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In the latest close session, MongoDB (MDB - Free Report) was up +2.86% at $366.49. The stock exceeded the S&P 500, which registered a gain of 0.33% for the day. Elsewhere, the Dow gained 1.08%, while the tech-heavy Nasdaq added 0.08%.

Shares of the database platform witnessed a loss of 5.33% over the previous month, trailing the performance of the Computer and Technology sector with its gain of 1.62%, and the S&P 500's gain of 1.41%.

The upcoming earnings release of MongoDB will be of great interest to investors. In that report, analysts expect MongoDB to post earnings of $1.6 per share. This would mark year-over-year growth of 21.21%. Our most recent consensus estimate is calling for quarterly revenue of $759.79 million, up 20.93% from the year-ago period.

For the entire fiscal year, the Zacks Consensus Estimates are projecting earnings of $6.5 per share and a revenue of $3.02 billion, representing changes of +30.78% and +22.69%, respectively, from the prior year.

Investors should also take note of any recent adjustments to analyst estimates for MongoDB. Such recent modifications usually signify the changing landscape of near-term business trends. Hence, positive alterations in estimates signify analyst optimism regarding the business and profitability.

Empirical research indicates that these revisions in estimates have a direct correlation with impending stock price performance. To benefit from this, we have developed the Zacks Rank, a proprietary model which takes these estimate changes into account and provides an actionable rating system.

The Zacks Rank system, running from #1 (Strong Buy) to #5 (Strong Sell), holds an admirable track record of superior performance, independently audited, with #1 stocks contributing an average annual return of +25% since 1988. Over the last 30 days, the Zacks Consensus EPS estimate has witnessed an unchanged state. MongoDB currently has a Zacks Rank of #1 (Strong Buy).

Looking at valuation, MongoDB is presently trading at a Forward P/E ratio of 54.85. For comparison, its industry has an average Forward P/E of 20.42, which means MongoDB is trading at a premium to the group.

It is also worth noting that MDB currently has a PEG ratio of 2.5. The PEG ratio is akin to the commonly utilized P/E ratio, but this measure also incorporates the company's anticipated earnings growth rate. The Internet - Software industry currently had an average PEG ratio of 1.18 as of yesterday's close.

The Internet - Software industry is part of the Computer and Technology sector. This group has a Zacks Industry Rank of 83, putting it in the top 34% of all 250+ industries.

The Zacks Industry Rank gauges the strength of our individual industry groups by measuring the average Zacks Rank of the individual stocks within the groups. Our research shows that the top 50% rated industries outperform the bottom half by a factor of 2 to 1.

Be sure to use Zacks.com to monitor all these stock-influencing metrics, and more, throughout the forthcoming trading sessions.

MongoDB Inc (NASDAQ:MDB), the US database software company, has retained a 'Buy' rating from Bank of America Securities and $540 price target, with the broker citing its long-term growth prospects in artificial intelligence and enterprise modernisation.

Analysts reaffirmed the rating following an investor meeting with management, highlighting MongoDB’s document-based database technology as a differentiated platform for businesses modernising their systems and developing AI applications.

The broker sees Atlas Infinite, MongoDB’s platform designed to let computing power and storage capacity scale independently, as a potential catalyst for adoption of AI workloads that require flexible infrastructure.

The platform is intended to support agentic artificial intelligence, in which software systems can perform tasks and take actions with limited human intervention, creating potential demand for databases that can respond to changing workloads.

Bank of America’s assessment reflects MongoDB’s long-term targets for annual revenue growth above 20% and generally accepted accounting principles (GAAP) profitability from 2027.

The broker raised its revenue forecasts for financial 2028 by 3% to $3.65 billion and for financial 2029 by 6% to $4.39 billion, reflecting greater confidence in the company’s growth trajectory.

It also increased its projected non-GAAP operating margins to 21.9% for financial 2028 and 22.9% for financial 2029, signalling expectations of improving profitability as revenue expands.

However, the leadership transition remains a near-term risk, while competition from traditional database providers such as PostgreSQL continues to shape investor debate over MongoDB’s competitive advantages.

Bank of America will monitor Atlas revenue growth and net revenue retention, which measures spending changes among existing customers, for evidence that Atlas Infinite is translating into sustained customer adoption.

The $540 price target reflects the broker’s confidence that MongoDB can combine AI-related demand with enterprise modernisation to deliver durable revenue growth and margin expansion.

It has been about a month since the last earnings report for MongoDB (MDB - Free Report) . Shares have lost about 7.1% in that time frame, underperforming the S&P 500.

Will the recent negative trend continue leading up to its next earnings release, or is MongoDB due for a breakout? Before we dive into how investors and analysts have reacted as of late, let's take a quick look at the most recent earnings report in order to get a better handle on the important catalysts.

MDB Q2 Earnings Beat Estimates on Atlas & EA Strength, Outlook RaisedMongoDB delivered second-quarter fiscal 2027 non-GAAP earnings of $1.90 per share, which rose 90% year over year and topped the Zacks Consensus Estimate by 18.75%.

Total revenues increased 30.5% year over year to $771.8 million and surpassed the consensus estimate by 5.2%. Results benefited from strength among large enterprise customers, solid Atlas consumption and broad Enterprise Advanced demand.

Total company net ARR expansion improved to 122% from 119% a year ago and 121% in the prior quarter.

MDB's Q2 Revenue Mix Reflects Broad StrengthSubscription revenues rose 30.5% year over year to $747.1 million, while services revenues increased 29.3% to $24.6 million. The subscription business remained the primary contributor to the top line.

Atlas-related revenues totaled $565.9 million, up 28.9% from $439.0 million a year ago. MongoDB Enterprise Advanced and other revenues reached $181.2 million, rising 35.9% from $133.4 million, reflecting broad strength across financial services, the public sector and technology.

MongoDB's Customer Metrics Keep ExpandingMongoDB ended the quarter with more than 70,600 customers, up from 59,900 a year ago, after adding approximately 2,900 customers sequentially. Atlas customers increased to more than 69,300 from 58,500 in the prior-year period.

Customers generating at least $100,000 in annual recurring revenues rose 17% year over year to 2,999. Among Atlas customers in this cohort, 48% used two or more platform features, up from 42%, driven largely by Vector Search and text search adoption. Remaining performance obligations climbed 91% to $1.52 billion.

MongoDB's Q2 Operating DetailsIn the fiscal second quarter, MongoDB’s non-GAAP gross profit increased to $585.7 million, with the non-GAAP gross margin expanding to 76% from 74% a year ago.

Subscription gross margin was 78.3%, up about 70 basis points, primarily reflecting the higher Enterprise Advanced revenue mix.

Non-GAAP sales and marketing expenses rose 6.9% year over year to $215.7 million. Research and development expenses increased 30.7% to $137.4 million, while general and administrative expenses advanced 9.6% to $46.7 million.

Non-GAAP income from operations rose to $185.9 million from $86.8 million. The corresponding operating margin expanded to 24% from 15%, underscoring stronger operating leverage alongside the quarter's revenue growth.

MongoDB's Balance Sheet & Cash FlowAs of July 31, 2026, MongoDB had cash, cash equivalents and short-term investments of $2.4 billion compared with $2.4 billion as of April 30, 2026.

During the quarter, the company allocated $100 million toward share repurchases and $59 million to settle taxes on employee restricted stock units.

Operating cash flow was $141.9 million in the fiscal second quarter compared with $201.6 million reported in the prior quarter.

Free cash flow during the quarter was $137.6 million compared with $197.5 million in the prior quarter.

MongoDB Raises Fiscal 2027 GuidanceFor the third quarter of fiscal 2027, MongoDB expects revenues of $756 million to $761 million. Non-GAAP income from operations is projected between $152 million and $156 million, while non-GAAP earnings are expected between $1.57 and $1.61 per share.

For fiscal 2027, revenues are now anticipated between $2.99 billion and $3.03 billion, up from the prior $2.92-$2.96 billion range. Non-GAAP earnings are projected between $6.39 and $6.58 per share compared with the previous $5.95-$6.14 range. Management now expects Atlas growth of approximately 27% and Enterprise Advanced and other revenue growth of about 11% for the year.

How Have Estimates Been Moving Since Then?It turns out, estimates revision have trended upward during the past month.

The consensus estimate has shifted 296.43% due to these changes.

VGM ScoresAt this time, MongoDB has a great Growth Score of A, a grade with the same score on the momentum front. However, the stock has a grade of F on the value side, putting it in the lowest quintile for this investment strategy.

Overall, the stock has an aggregate VGM Score of C. If you aren't focused on one strategy, this score is the one you should be interested in.

OutlookEstimates have been broadly trending upward for the stock, and the magnitude of these revisions looks promising. It comes with little surprise MongoDB has a Zacks Rank #1 (Strong Buy). We expect an above average return from the stock in the next few months.

Performance of an Industry PlayerMongoDB is part of the Zacks Internet - Software industry. Over the past month, Rubrik, Inc. (RBRK - Free Report) , a stock from the same industry, has gained 31.3%. The company reported its results for the quarter ended July 2026 more than a month ago.

Rubrik, Inc. reported revenues of $427.26 million in the last reported quarter, representing a year-over-year change of +37.9%. EPS of $0.20 for the same period compares with -$0.03 a year ago.

For the current quarter, Rubrik, Inc. is expected to post earnings of $0.09 per share, indicating a change of -10% from the year-ago quarter. The Zacks Consensus Estimate has changed -0.4% over the last 30 days.

The overall direction and magnitude of estimate revisions translate into a Zacks Rank #3 (Hold) for Rubrik, Inc.. Also, the stock has a VGM Score of C.

MongoDB Inc (NASDAQ:MDB) raised its long-term growth targets at its investor day, with Bank of America saying the event was a net positive and maintaining its Buy rating on the stock.  

For fiscal 2028 to 2030, the database company now targets total revenue growth of 20% or more, up from the high teens. It lifted its Atlas growth target to the mid-20% range from 20% or more, and its Enterprise Advanced (EA) ARR growth target to 10% or more from low-to-mid single digits.  

The company also kept its goal of 100 to 200 basis points of annual non-GAAP operating margin expansion. 

The news caused MongoDB shares to claw back some of its earlier losses this week after a surprise CEO shakeup. Chirantan "CJ" Desai left to lead a new Meta division, while MongoDB appointed Dev Ittycheria interim CEO. 

Shares were up 4.5% on Wednesday. 

At the investor day, management tied the higher targets to identifiable drivers, including enterprise AI workloads, AI-native adoption, product innovation, application modernization and partnerships, the BofA analysts said in a note. They expect the new targets to push consensus growth and profitability forecasts higher, since current forecasts sit below the long-term goals. 

The standout disclosure, according to BofA, was that AI-native customers now account for 3% to 5% of Atlas revenue. That revenue grew 165% year over year in the fiscal second quarter of 2027, accelerating from 129% growth in the same quarter a year earlier. 

About 40% of Atlas annual recurring revenue now comes from customers with at least one AI use case, up from roughly 30% a year ago. The AI-native customer base has also grown to more than 2,200, an increase of over 500 from a year ago. 

MongoDB also highlighted new and expanded offerings, including Atlas Agent Engine, which extends the company's role beyond the database and memory layer into agent deployment.  

The firm said near-term execution remains a risk as the leadership transition unfolds, as does the question of whether growing AI adoption converts into large production deployments and meaningful Atlas revenue rather than staying in experimentation and pilot workloads. 

Atlas Agent Engine unifies governance, memory, and retrieval, ending the choice between a stitched-together stack and being locked into one vendor's model and cloud

, /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today launched Atlas Agent Engine, a unified execution, memory, and governance layer for production AI agents, at its Investor Day at the Nasdaq MarketSite in New York City. While AI agents prove their value quickly in proof-of-concept testing, bringing them into production remains a major bottleneck. Doing so requires accurate retrieval, persistent memory, and enterprise-grade security and governance. Without a single platform, engineering teams must stitch together disparate tools that break every time underlying models or frameworks evolve. That's what Atlas Agent Engine is designed to solve for.

"Investigating unusual activity in our payment network today means our analysts stitching together data from multiple systems by hand, often under time pressure. We're excited about the potential for an intelligent agent, built on MongoDB's Atlas Agent Engine, to shrink the time between a problem emerging and our team acting on it, giving our analysts more time to focus on the judgment calls that matter most," said Amar Akshat, SVP of Architecture, Paysafe.

Atlas Agent Engine is available today in public preview. New and existing Atlas customers can get started at agentengine.mongodb.com.

Atlas Agent Engine gives teams a modular way to put agents into production. Retrieval is powered by MongoDB Voyage AI, whose embedding and reranking models rank among the top performers on RTEB, a benchmark built to reflect real enterprise retrieval instead of academic datasets. Customers can adopt the memory and governance layers independently or with the runtime, using existing models and frameworks they know. Atlas Agent Engine is available today in public preview, with consumption-based pricing for Atlas Agent Runtime and Atlas Agent Memory. Usage draws on customers' existing Atlas commitments, so adoption extends infrastructure already in place rather than requiring a new contract.

"Context is the critical success factor in successfully using agents for application development. Enterprises are currently struggling to assess, integrate and manage information across multiple systems to enable an ontology for autonomous agentic work." said James Governor, co-founder of RedMonk. "MongoDB Atlas Agent Engine is designed to bake governance into agentic app development with a single platform for memory and identity."

Atlas Agent Engine is built with the ecosystem enterprises already trust. Frontier Labs bring the best available models directly to where enterprise data already lives. System integrator partners bring the industry expertise and delivery experience customers rely on for agent deployments.

"Atlas Agent Engine brings the enterprise-ready capabilities, context, and constraints needed to help AI agents deliver real-world impact. Combined with Accenture's governance, architecture, and deep industry expertise, it creates a powerful foundation for accelerating AI transformation and delivering outcomes at scale. Our shared commitment to delivery and customer success makes this partnership particularly strong," said Ram Ramalingam, Global Lead, SW Engineering & Head of RDE Accenture.

Built to get agents into production

Enterprises building agents often run into the same three challenges: actions nobody can govern, agents that forget, and lock-in to a single model or framework. Atlas Agent Engine solves all three, grounded in the same operational platform that more than 70,000 customers already run on, with enterprises like Paysafe already building toward production.

"Organizations that want to put agents in production are being forced into a false tradeoff: either adopt one vendor's runtime and accept being locked into a model and cloud, or piece together a framework and manage governance and memory on their own," said Pablo Stern-Plaza, Chief Product Officer, AI and Emerging Products, MongoDB. "With the launch of Atlas Agent Engine, that false tradeoff ends today. Enterprises get the real-time context their agents need, with governance and security built in from the start, and the freedom to run any model, any framework, and on any cloud. We didn't want to ask customers to predict the future. We wanted to build something that works no matter what they choose."

Governed by default. Most platforms handle identity, audit, guardrails, and cost controls as separate systems teams have to stitch together themselves. Atlas Agent Engine puts it all behind one control plane: every action is logged against a real identity, human or agent, and governed by policy that can't be quietly switched off. Governance is built in, not bolted on after launch. So when someone asks what an agent did and who authorized it, the answer takes seconds, not weeks. And because governance, memory, and retrieval run as one system instead of stitched-together services, there's less to secure and fewer places for things to break.

Memory and retrieval built in. Without built-in memory, agents start every conversation from zero, and teams end up rebuilding memory infrastructure for every new agent. Atlas Agent Engine builds memory into the platform itself, using Voyage AI embeddings and MongoDB's native retrieval, so agents get more accurate while spending fewer tokens.

Open design. Standardizing on one model, cloud, or framework is one of the riskiest infrastructure bets a leader can make in a market that moves this fast. Atlas Agent Engine is neutral across AI models and frameworks. Because it's built on open standards like MCP and A2A, changing course later only takes a configuration change rather than an expensive rebuild. It will also run across any cloud, self-managed or even a laptop, so the same agent works everywhere without rebuilding cloud by cloud. Atlas Agent Engine adds governed execution, memory, and cost control on top of what teams already run, rather than asking them to replace it.

MongoDB is committed to giving customers the openness and security they need. We are joining the Linux Foundation's Open Secure AI Alliance and Agentic AI Foundation to drive open software and standards for secure, interoperable agents—so organizations can move agents into production with the flexibility and control to scale as their needs evolve.

Atlas Agent Engine, MongoDB 9.0, and Atlas Infinite, also announced today, build on each other: MongoDB 9.0 strengthens the foundation every MongoDB customer already runs on, Atlas Infinite removes the limits on how that foundation can scale, and Atlas Agent Engine puts AI agents to work on top of both, governed and grounded in real-time data. Together with Voyage AI's industry-leading embedding and retrieval models, already generally available, this extends MongoDB's intelligent data platform for the AI era. To learn more about all three new launches and everything else MongoDB announced at Investor Day, please visit https://www.mongodb.com/company/newsroom.

About MongoDB
MongoDB is the intelligent data platform for the AI era. Headquartered in New York, MongoDB helps organizations move faster, build smarter, and simplify complex architectures on a unified platform for operational data, search, real-time analytics, and AI-powered retrieval, coupled with MongoDB Voyage AI's industry-leading embedding and reranking models. The platform is available as a fully managed service with MongoDB Atlas or self-managed with MongoDB Enterprise Advanced or Community Edition. Millions of developers and more than 70,000 customers, including approximately 75% of the Fortune 100, rely on MongoDB for their most important customer-facing applications. To learn more, visit mongodb.com.

Forward-Looking Statements

This press release includes certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including new capabilities announced at MongoDB.local NYC Investor Day 2026. These forward-looking statements include, but are not limited to, plans, objectives, expectations and intentions and other statements contained in this press release that are not historical facts and statements identified by words such as "anticipate," "believe," "continue," "could," "estimate," "expect," "intend," "may," "plan," "project," "will," "would" or the negative or plural of these words or similar expressions or variations. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including, without limitation, those more fully described in our filings with the Securities and Exchange Commission ("SEC"), including under the caption "Risk Factors" in our most recent Quarterly Report on Form 10-Q filed with the SEC. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

Contacts

Investors: [email protected]

Media: [email protected]

SOURCE MongoDB, Inc.

Devin for MongoDB Modernizations helps get customers off legacy infrastructure faster, so engineering teams spend less time maintaining old code and more time building on MongoDB Atlas

, /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) and Cognition, the company behind Devin, the AI software engineer, today announced the launch of Devin for MongoDB Modernizations. Modernization is often a necessary first step for enterprises building AI-powered applications, but legacy infrastructure can hamper many modernization efforts because it is expensive to maintain and difficult to scale. This partnership connects Devin directly to MongoDB's Application Modernization Platform (AMP), meeting customers wherever they are on their modernization journey and accelerating their path onto MongoDB—the intelligent data platform for the AI era.

Devin connects directly to AMP's tooling, which moves and validates data into Atlas, giving joint customers a faster, more automated path from legacy code to production on Atlas. By using Devin and MongoDB together, customers can significantly reduce migration timelines and free up engineering teams to build on MongoDB Atlas, the company's multi-cloud intelligent data platform, instead of working around legacy code that was never designed for it.

"At Bilt, we used Devin to rebuild search and personalization on MongoDB, allowing members to use natural-language queries to discover businesses, services and experiences across our growing ecosystem," said Kosta Krauth, CTO, BILT. "During the final push, our engineering team averaged dozens of merged pull requests a day, while Devin's connection to Atlas's managed MCP service helped us keep testing moving just as quickly. We're excited to see Cognition and MongoDB make it easier to build more experiences like this."

When planning a migration, customers need to balance multiple workstreams: rewriting the business logic that ties code to old data, and moving that data itself. Devin for MongoDB Modernizations assigns each piece to what it does best—Devin handles the code, planning, and rewriting of business logic and data access layers case by case, while AMP's deterministic tooling moves and validates each record into MongoDB—and orchestrates the full process end to end, so customers experience one coordinated migration instead of a patchwork of scripts and manual handoffs. Engineering teams retain control over the decisions that require human judgment, like designing the target data model and sequencing the cutover, while Devin and AMP handle the rest. Teams not yet on MongoDB can get started with Atlas for free at mongodb.com/atlas.

Why Devin for MongoDB Modernizations

Legacy migrations to MongoDB rarely stall due to the new database. They stall due to the wiring around the legacy code. Untangling the thousands of queries, stored procedures, and data access layers takes judgment that no script can supply and is exactly the kind of work Devin is built for.

"Even the most ambitious engineering teams spend much of their capacity keeping legacy systems alive. Devin for MongoDB Modernizations solves that pain. Devin does the heavy lifting, rewriting code across the codebase, so customers reach production on MongoDB in weeks instead of years. Engineers can get back to building great software and solving hard problems," Scott Wu, Co-founder and CEO, Cognition.

Extending MongoDB's Application Modernization Platform

The partnership with Cognition also strengthens AMP, which helps enterprises move onto MongoDB across four phases:

Understanding what a legacy infrastructure does and how to sequence its migration Transforming its code Migrating its data Verifying that the modernized application matches the original Devin's code transformation and agentic orchestration extend AMP's language coverage and lets its tools run with fewer manual handoffs between steps. In early joint testing, that shows up directly in the numbers - work that used to take five to six hours now takes just over an hour.

"Most enterprises know they need to modernize their legacy applications, but the cost, complexity, and sheer amount of code involved have forced them to do it one application at a time," said Dev Ittycheria, CEO of MongoDB. "AMP was built to change the economics of modernization by giving customers an automated path from legacy applications to MongoDB. By integrating Devin's code transformation and agentic capabilities into AMP, we can automate even more of that journey and dramatically expand the amount of an enterprise's application estate that can be modernized at once. The result is bigger than a faster migration. Customers can move decades of legacy applications onto MongoDB in months instead of years, giving them a modern data foundation built to run AI applications and agents in production on live operational data."

Devin for MongoDB Modernizations is available now to MongoDB and Cognition customers. To learn more or request an engagement, visit mongodb.com/company/partners/cognition. 

About MongoDB
MongoDB is the intelligent data platform for the AI era. Headquartered in New York, MongoDB helps organizations move faster, build smarter, and simplify complex architectures with a unified platform for operational data, search, real-time analytics, and AI-powered retrieval, coupled with MongoDB Voyage AI's industry-leading embedding and reranking models. The platform is available as a fully managed service with MongoDB Atlas or self-managed with MongoDB Enterprise Advanced or Community Edition. Millions of developers and more than 70,000 customers, including approximately 75% of the Fortune 100, rely on MongoDB for their most important customer-facing applications. To learn more, visit mongodb.com.

About Cognition
Cognition is the leading AI software engineering company and makers of Devin, the world's first AI software engineer. Devin works end-to-end on complex engineering tasks — planning, coding, testing, and iterating autonomously — enabling teams to scale their engineering capacity without scaling headcount. Cognition has raised over $2B at a $48B valuation and partners with leading enterprises across financial services, technology, and beyond.

Investors: [email protected]
Media: [email protected]

SOURCE MongoDB, Inc.

Bank of America expects MongoDB Inc (NASDAQ:MDB)'s investor day on September 29 to provide a potential catalyst for the shares, with artificial intelligence (AI) adoption metrics and higher long-term targets among the key areas to watch.

The broker said quantitative evidence that AI is improving customer acquisition or consumption could strengthen the investment case, while updates on Model Context Protocol (MCP) adoption and stronger financial targets could support a higher valuation.

BofA maintained its 'Buy' rating and $540 price target, which implies about 40% upside, saying MongoDB trades at 8.6 times estimated 2027 enterprise value to revenue, a 43% discount to its established AI-beneficiary peer average of 15.2 times.

MongoDB has delivered sustained Atlas growth of 29% year on year over the past five quarters, while Enterprise Advanced (EA) is emerging as a second growth engine and profitability has continued to exceed expectations.

BofA said EA revenue could broaden MongoDB's customer footprint, with demand supported by data sovereignty, cloud capacity, governance and regulatory requirements.

EA annual recurring revenue grew about 11% in the second quarter of fiscal 2027, marking its third consecutive quarter of double-digit growth, while reported revenue increased 30.5% from a year earlier.

The broker said customers using both Atlas and EA generate above-average Atlas consumption growth, suggesting EA could support expansion while helping fund further investment.

BofA said AI consumption data would be the clearest potential upside catalyst, while growth in Voyage and Vector Search and adoption of MCP could provide additional evidence of AI-driven demand.

MongoDB added a record 2,900 customers in the second quarter, while Voyage customers roughly doubled sequentially and Vector Search adoption outpaced overall company growth, according to Bank of America.

The broker said higher three-to-five-year financial targets could further strengthen confidence in MongoDB's growth prospects, with current targets of high-teens revenue growth and operating margins above 20% appearing conservative against fiscal 2027 guidance.

MarketBeat Week in Review – 09/07 - 09/11MongoDB NASDAQ: MDB CEO CJ Desai outlined the company’s focus on enterprise modernization, AI-native customers and product enhancements during Citi’s TMT Conference, following what he described as a strong fiscal second-quarter report.

Desai said MongoDB reported total revenue growth above 30% in the quarter, marking what he called the company’s first time reaching that growth level “in a long time.” He also said the company is pursuing durable growth alongside increasing profitability, citing operating-margin and cash-flow results released the prior week.

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Could Snowflake's Big Quarter Be a Sign of More to Come?After roughly a year as CEO, Desai said he sees three primary areas of opportunity: broader enterprise adoption, demand from AI-native companies and early engagement with frontier AI labs.

Enterprise modernization and global demand Desai said MongoDB is increasingly becoming a standard platform for modern database deployments at large enterprises, particularly in financial services and insurance, where companies are managing unstructured data and moving toward multicloud environments.

AI Token Costs Are Changing the Hardware vs. Software DebateHe also cited early public-sector demand and international opportunities. In Europe, he said sovereign-cloud requirements have supported demand for MongoDB’s ability to be self-managed and deployed across environments. In India, Desai pointed to digital-native companies, including Zomato, that are building on MongoDB.

The company is also putting greater emphasis on executive-level relationships with chief information officers, chief technology officers, chief data officers and enterprise architects. Desai said some large customers spending seven- or eight-figure annual recurring revenue amounts had not fully recognized the extent of their MongoDB usage across mission-critical workloads.

Those conversations are also opening opportunities around AI readiness and modernization, according to Desai. He said MongoDB is discussing ways to help enterprises migrate certain workloads from aging relational databases, with the goal of reducing migration projects from years to months or from months to weeks.

AI-native customers and frontier labs Desai said many AI-native companies initially used PostgreSQL or hyperscaler-provided database services before encountering scaling constraints and moving to MongoDB. He said companies such as Mercor, ElevenLabs and Harvey have become examples of businesses using MongoDB as a foundational operational data layer.

He identified three product attributes that he believes are driving adoption for AI workloads:

MongoDB’s JSON-native document model, which Desai said aligns with the structure and speed of AI development; Its ability to scale out for large workloads; and Its ability to run across cloud environments, including configurations spanning multiple hyperscalers. For AI labs, use cases vary, Desai said. One example involves using MongoDB as a conversational memory layer for agent interactions. At ElevenLabs, he said MongoDB supports real-time agent workloads involving speech-to-text, text-to-speech and significant volumes of unstructured data.

Desai said enterprise adoption of customer-facing AI agents remains earlier than adoption of internal-facing AI applications. He expects technology companies, including cybersecurity providers, to be among the earlier enterprise adopters of external-facing agent deployments. Retail and financial services could follow, he said, while manufacturing and consumer packaged goods may take longer.

Atlas, developer tools and customer additions Addressing investor attention on Atlas growth, Desai said MongoDB’s core business differs from data warehouse and observability peers because its workloads are generally customer-facing rather than employee-facing. He said Atlas consumption could increase as enterprises deploy customer-facing agents at scale.

The company recently introduced automatic embeddings capabilities using Voyage AI and launched generally available fully managed Model Context Protocol functionality for Claude Code, Codex and Grok Build on Aug. 13, according to Desai. He said MongoDB had seen higher Atlas traffic in the roughly three-and-a-half weeks after the MCP launch and expects to provide additional information at its Investor Day on Sept. 29.

Desai said the fully managed MCP functionality could make it easier for developers to build and provision Atlas clusters through coding-agent tools. He also said Voyage customer additions have been strong, with many referrals coming from Claude Code and Codex. MongoDB sees those Voyage users as a potential top-of-funnel opportunity for Atlas.

The company added approximately 2,900 customers, its highest quarterly level, according to the conference discussion. Desai said about 99% of new customer additions are on Atlas. He added that MongoDB is focused on attracting workloads that can scale meaningfully rather than prioritizing lower-scale internal applications.

Go-to-market priorities and migrations Head of Investor Relations Jess Lubert said MongoDB continues to see particular strength among its largest North American customers. She identified U.S. federal and Asia-Pacific as areas for improvement. The company is investing in FedRAMP High and sees Japan as a significant database market, while making go-to-market changes across Asia.

Desai said MongoDB’s net revenue retention rate was 122%, with both self-managed and Atlas offerings contributing healthy retention results.

On database migrations, Desai said MongoDB is shifting from a services-heavy approach to a more product-driven strategy. The company is working with large design partners to improve tools that can migrate workloads from relational databases to Atlas more quickly. He said MongoDB expects to invest more heavily behind that effort in the next fiscal year once the product is ready.

Looking ahead, Desai said MongoDB’s priorities are to remain the best database across self-managed and Atlas deployments, make MongoDB more appealing to coding agents and establish the platform as a default real-time operational data layer for AI workloads.

About MongoDB (NASDAQ:MDB)MongoDB, Inc develops database software and data platform services for organizations building, deploying and operating modern applications. Its flagship technology is a document-oriented database that stores data in flexible, JSON-like documents, helping developers manage varied data structures and support applications that require scalability and rapid development.

The company offers MongoDB Atlas, a fully managed cloud database service available across major cloud providers, as well as MongoDB Enterprise Advanced for organizations that operate databases in private, hybrid or multicloud environments.

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Should You Invest $1,000 in MongoDB Right Now?Before you consider MongoDB, you'll want to hear this.

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MongoDB MDB is experiencing a significant drop in pre-market trading, even after reporting a strong Q2 performance that exceeded expectations. Investors are concerned about the slowdown in Atlas growth, which decreased from approximately 29% to a projected 26% for Q3, along with an anticipated further moderation in Q4. Although management raised its FY27 Atlas growth forecast by 300 basis points to around 27%, the overall guidance for Q3 includes an EPS estimate of $1.57-$1.61 and revenue expectations of $756-$761 million. Additionally, FY27 guidance has been lifted to an EPS range of $6.39-$6.58 and revenue of $2.99-$3.03 billion. However, these positive updates did not meet the high expectations reflected in the stock's near 52-week high trading levels.

Atlas achieved a record revenue increase of $127 million year-over-year, marking the sixth consecutive quarter of growth. The company-wide net Annual Recurring Revenue (ARR) expansion rate rose to 122% from 121% sequentially, with contributions from both Atlas and Enterprise Advanced (EA). Remaining Performance Obligations (RPO) surged 91% to $1.52 billion, while current RPO grew by 73%. However, this growth is influenced by multiyear EA agreements and does not directly indicate Atlas consumption. EA and other revenue increased by approximately 36%, with FY27 growth guidance revised up to about 11%, compared to a previous mid-single-digit forecast. Nonetheless, management expects EA growth to remain in the mid-single digits for Q3 and flat for the latter half of the year due to unpredictable deal timing. MDB welcomed a record 2,900 new customers, bringing the total to 70,600. Customers generating at least $100,000 in ARR increased by 17% to nearly 3,000, and Voyage customers doubled sequentially for the second consecutive quarter. Non-GAAP operating margin improved to 24% from 15%, while gross margin rose by 210 basis points to 75.9%, partly due to a higher proportion of profitable EA revenue. MDB anticipates around 250 basis points of operating margin expansion for FY27, but Q3 margin guidance suggests that Q2 should not be viewed as the new run rate.The key issue lies in the market's high expectations for MDB's Atlas growth trajectory, despite the company improving its annual growth and profitability outlook. Management indicated that consumption trends remain steady, with Q3 presenting the toughest year-over-year comparison. Recent quarterly Atlas guidance has exceeded expectations by 200-300 basis points, suggesting that the projected Q4 slowdown may be conservative. However, visibility on consumption diminishes beyond one quarter, and holiday activities could impact Q4 usage. Additionally, EA's multiyear contracts contribute to revenue variability. While AI adoption bolsters the long-term platform strategy, investors are seeking assurance that Voyage, Vector Search, and production agents can generate significant revenue. Upcoming evaluations will focus on Atlas consumption from September to October, EA deal conversions, multi-product adoption, and MDB's execution against its targeted Rule-of-44 profile.

This stock alert was generated using automated technology and GuruFocus financial data to provide readers with timely and accurate market reporting. This content was reviewed by GuruFocus editorial team prior to publication. Please send any questions or comments about this story to [email protected].

Disclosures I/We may personally own shares in some of the companies mentioned above. However, those positions are not material to either the company or to my/our portfolios.

Live 6 updates · Last at 4:51pm ET Updates appear automatically.

By Thomas Richmond · Updated Sep 1, 4:51pm ET · Published Sep 1, 3:04pm ET

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Live UpdatesNewest first

That wraps up our initial coverage of MongoDB’s results. Thank you for stopping by!

MongoDB just reported earnings, with shares initially down 13% following the report. Here are the key numbers:

Revenue: $772 million vs. $734 million expected Adjusted EPS: $1.90 vs. $1.61 expected RPO: $1.52 billion, up 91% year over year Atlas Revenue: $566 million, up 29% year over year Guidance:

FY27 Revenue: $3.01 billion vs. $2.96 billion expected FY27 EPS: $6.49 vs. $6.13 expected Quick Read:

A strong beat-and-raise isn’t enough: MongoDB topped revenue and EPS expectations and lifted its full-year outlook above consensus, yet shares initially plunged 13%. Atlas growth remains strong at 29%: With RPO surging 91%, the selloff suggests expectations and valuation were simply extremely high after the stock’s sharp run into earnings, rather than an obvious deterioration in headline fundamentals.

Wall Street models Q2 revenue near and EPS of , sitting right at the top of MongoDB‘s (NASDAQ:MDB) own guide of and . CFO Mike Berry said guidance while staying a framework that produced .

Bullish: FY27 revenue lifted above , Atlas sustained near , and full-year EPS raised above .

Bearish: An unchanged FY27 range, Atlas decelerating below 27%, or a Q3 view soft versus the consensus.

CFO Mike Berry noted Atlas has as it scales. RPO of , up year over year, gives management cover to raise. Anything less than a confident raise risks a repricing.

Ahead of tonight’s MongoDB (NASDAQ:MDB) earnings release, here’s the analyst playbook for the call.

Top 5 Analyst Questions Can Atlas sustain as it laps tougher comps? What is real revenue contribution from Voyage AI, Vector Search, and agent memory? How durable is as forward visibility? Federal traction after the Clarity Business Solutions acquisition? Path to consistent GAAP profitability given stock-based comp? Key Topics Management Must Address Magnitude of the FY27 raise above Enterprise Advanced decline trajectory Progress under CEO CJ Desai and new CPOs Buzzwords to Listen For Rule of 40, agentic AI, unified data platform, consumption trends, mission-critical workloads Red Flags Atlas below 29%, softer Q3 guide, slowing customer adds, or macro caution commentary

Bull Case: Why MongoDB Could Beat and Rally Atlas grew in Q1 with RPO up to , signaling durable forward visibility. Polymarket assigns a probability of a beat, backed by upward EPS revisions and zero cuts in 30 days. Agentic AI wins with Adobe (NASDAQ:ADBE), , and validate Atlas as a scaled AI backend for enterprise workloads. Bear Case: Why the Setup Looks Stretched Shares are up in a month, leaving little margin for error. Q4 FY26 topped estimates by , yet shares plunged on guidance concerns. Q3 FY27 consensus saw downward EPS revisions, hinting at a softer second-half setup. Leadership turnover adds execution risk against elevated expectations.

MongoDB is expected to report Q2 FY27 earnings at 4:05 PM ET, with management guiding for $729-$734 million in revenue. The bigger question is whether Atlas can sustain the roughly 26% growth management has targeted for the quarter.

Expectations have risen sharply. MongoDB shares are up 34.34% over the past month, while Polymarket traders are assigning a 97.1% probability that the company beats expectations.

That makes guidance especially important. A strong quarter accompanied by a raise that pushes FY27 revenue above $2.96 billion would strengthen the case that MongoDB is becoming a major beneficiary of agentic AI and growing database demand.

In Q4 of FY26, MongoDB topped expectations by 12.08%, yet shares still plunged 22.24%. With the stock rallying into tonight’s print, investors will likely demand both strong results and an improving outlook.

This article is updated throughout the trading day. Check back for more.

Full CoverageThe story so far

MongoDB (NASDAQ:MDB | MDB Price Prediction) reports Q2 FY27 results today at 4:05 PM ET. The database platform enters the report with a $35.9 billion market cap, with the stock down 3.5% today.

Momentum Meets a Higher Bar Last quarter, MongoDB posted $687.6 million in revenue, up 25.25% year over year, and non-GAAP EPS of $1.32 versus a $1.1835 consensus.

Atlas, now roughly 75% of revenue, grew 29.4% and crossed a $2 billion run rate. Free cash flow nearly doubled to $197.5 million, and RPO jumped 88% to $1.46 billion. CEO CJ Desai raised full-year guidance on that strength. Shares have followed through, with MDB rising 43.65% over the past year and trading at $437.47 into the report.

Consensus Estimates Metric Q2 FY27 Estimate YoY Change FY27 Estimate FY28 Estimate Revenue $734.4M +24% $2.96B $3.48B EPS (Normalized) $1.609 +145% $6.13 $7.34 The Q2 EPS bar has climbed from $1.28 ninety days ago to $1.609, with 34 upward revisions in the past 30 days and zero cuts. Consensus now sits above the guidance midpoint, meaning MongoDB effectively needs to clear its own top end to keep the beat streak intact.

What I’m Watching Tonight: Atlas Consumption, AI Workloads, and Margin Leverage Tonight, I’ll be watching Atlas consumption first. Management guided Q2 Atlas growth to approximately 26%, a deceleration from 29.4%, and CFO Mike Berry described the segment as “more predictable and less sensitive” at scale. Any reacceleration reframes the multiple.

Second, analysts are of course going to be watching AI traction. Desai said “AI adoption of MongoDB technologies across our customer base continues to accelerate,” with vector search “far outpacing overall company growth.” New Adobe, Zomato, and 11 Labs deployments should give management fresh proof points.

Third, margins. Non-GAAP operating margin expanded to 18% from 16%, and the company targeted approximately 21% at the Q2 high end. Rule of 40 status is on the line.

Fourth, EA. Enterprise Advanced grew 13% last quarter, but management guided to approximately flat EA growth in the second half. Deal timing commentary matters.

Finally, the Clarity acquisition and federal push. Investors want scope on the $10 million annual services contribution and pipeline build.

Earnings History Quarter EPS Surprise Day-Of Move 1-Day Move 1-Week Move Q1 FY27 +11.53% +3.03% +20.36% +4.53% Q4 FY26 +12.08% -22.24% -1.87% +7.05% Q3 FY26 +66.23% +22.23% +0.98% +3.00% Q2 FY26 +52.39% +37.96% +7.58% +8.91% On average, shares moved 3.39% seven days after earnings over the past year.

Contact [email protected] for any questions or corrections.

Thomas Richmond

Thomas Richmond is a financial writer and content strategist with 5+ years of experience covering stocks and financial markets. He has published over 250 articles focused on individual stock analysis, helping investors better understand business fundamentals, stock valuations, and long-term opportunities.

Thomas previously served as a Content Lead at TIKR, a stock research platform, where he helped scale the company’s blog to hundreds of articles per month and contributed to a weekly newsletter reaching more than 100,000 investors.

He specializes in breaking down complex companies into clear, actionable insights for everyday investors, with a focus on fundamentals-driven research.

His work has also been featured on platforms including Seeking Alpha and Sure Dividend.

Outside of work, Thomas enjoys weight lifting and soccer.

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MongoDB, Inc. (NASDAQ:MDB) will release its second earnings report after the closing bell on Tuesday, Sept. 1.

Analysts expect the New York-based company to report quarterly earnings of $1.61 per share, up from $1.00 per share in the year-ago period. The consensus estimate for MongoDB’s quarterly revenue is $734.4 million. It reported $591.4 million last year, according to Benzinga Pro.

On May 28, MongoDB reported better-than-expected first-quarter financial results and issued second-quarter guidance above estimates.

MongoDB shares gained 1.4% to close at $446.62 on Friday.

Benzinga readers can access the latest analyst ratings on the Analyst Stock Ratings page. Readers can sort by stock ticker, company name, analyst firm, rating change or other variables.

Let’s have a look at how Benzinga’s most-accurate analysts have rated the company in the recent period.

DA Davidson analyst Rudy Kessinger maintained a Buy rating and raised the price target from $375 to $465 on Aug. 26, 2026. This analyst has an accuracy rate of 75%. Barclays analyst Raimo Lenschow maintained an Overweight rating and boosted the price target from $387 to $460 on Aug. 26, 2026. This analyst has an accuracy rate of 71%. Wells Fargo analyst Ryan Macwilliams maintained an Overweight rating and raised the price target from $375 to $475 on Aug. 25, 2026. This analyst has an accuracy rate of 67%. Baird analyst William Power maintained a Neutral rating and boosted the price target from $335 to $400 on Aug. 25, 2026. This analyst has an accuracy rate of 84%. UBS analyst Karl Keirstead maintained a Neutral rating and increased the price target from $350 to $460 on Aug. 24, 2026. This analyst has an accuracy rate of 75%. Trending

Considering buying MDB stock? Here’s what analysts think:

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In its upcoming report, MongoDB (MDB - Free Report) is predicted by Wall Street analysts to post quarterly earnings of $1.60 per share, reflecting an increase of 60% compared to the same period last year. Revenues are forecasted to be $733.61 million, representing a year-over-year increase of 24%.

The current level reflects no revision in the consensus EPS estimate for the quarter over the past 30 days. This demonstrates how the analysts covering the stock have collectively reappraised their initial projections over this period.

Prior to a company's earnings release, it is of utmost importance to factor in any revisions made to the earnings projections. These revisions serve as a critical gauge for predicting potential investor behaviors with respect to the stock. Empirical studies consistently reveal a strong link between trends in earnings estimate revisions and the short-term price performance of a stock.

While investors typically rely on consensus earnings and revenue estimates to gauge how the business may have fared during the quarter, examining analysts' projections for some of the company's key metrics often helps gain a deeper insight.

In light of this perspective, let's dive into the average estimates of certain MongoDB metrics that are commonly tracked and forecasted by Wall Street analysts.

Analysts' assessment points toward 'Revenue- Subscription' reaching $710.67 million. The estimate suggests a change of +24.2% year over year.

The consensus among analysts is that 'Revenue- Services' will reach $21.90 million. The estimate indicates a year-over-year change of +15%.

The average prediction of analysts places 'Revenue- Subscription - Atlas-related' at $552.44 million. The estimate suggests a change of +25.9% year over year.

Analysts expect 'Revenue- Subscription - MongoDB Enterprise Advanced and other' to come in at $159.26 million. The estimate points to a change of +19.4% from the year-ago quarter.

The collective assessment of analysts points to an estimated 'MongoDB Atlas customers' of 68,939 . Compared to the present estimate, the company reported 58,300 in the same quarter last year.

View all Key Company Metrics for MongoDB here>>>

Over the past month, MongoDB shares have recorded returns of +26.5% versus the Zacks S&P 500 composite's +3.7% change. Based on its Zacks Rank #3 (Hold), MDB will likely exhibit a performance that aligns with the overall market in the upcoming period. You can see the complete list of today's Zacks Rank #1 (Strong Buy) stocks here >>>> .

A new Managed MCP Server connects Claude Code, Codex, Grok Build, and Devin to MongoDB Atlas, giving coding agents direct access to live operational data

, /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today announced at MongoDB.local Build Fest that MongoDB's intelligent data platform is now available natively inside the AI tools developers use to build applications. Available today, MongoDB Atlas Managed MCP Server is a fully hosted way to connect agents to Atlas without running additional infrastructure. Builders can now easily add MongoDB Atlas to Claude Code, Codex, Grok Build and Devin. Everything announced today is available now, and teams can get started with Atlas for free at mongodb.com/atlas.

"The AI tools teams reach for keep changing, so our approach is to make sure MongoDB is present in all of them, whether a team is working in Claude or Codex, or running an agent in production. More of that building is now done by agents, and neither the agent nor the developer has to stop and set up a connection, so applications come together faster," said Pablo Stern-Plaza, Chief Product Officer, AI and Emerging Products, MongoDB.

With the new connectors, MongoDB is available natively across the tools where software is built. Ask questions of data in plain language in ChatGPT, Claude, and Grok. Query, inspect, and update data in MongoDB as work happens, with coding agents like Claude Code, Codex, Grok Build and Devin. And builders can also see live MongoDB data while generating an app in an IDE like Cursor. 

Getting connected with these tools takes only a few clicks. Find the MongoDB connector in the tool's marketplace and authorize it, with no connection string to paste and no infrastructure to configure. Once connected, the tool can list collections and indexes, query and aggregate data, and inspect schemas—and with the right permissions—can also create collections or manage indexes.

Introducing the MongoDB Atlas Managed MCP Server

Running an agent in production means connecting it to real operational data and agent memory, and until now, teams had to build and maintain that connection themselves. MongoDB's MCP server already sees more than 30,000 installs a week. Starting today, the MongoDB Atlas Managed MCP Server is remote and fully hosted, running as a service inside Atlas, so there is nothing for a team to install, operate, or upgrade. Teams connect using the same credentials and access controls they already use with Atlas, so administrators can govern how agents access operational data from one place.

"Developers want their AI tools to connect with the context and systems they already rely on," said Vibhor Chhabra, Product Lead for ChatGPT Ecosystem at OpenAI. "MongoDB's plugin in ChatGPT makes it easier to access and work with live application data, helping developers move faster while staying grounded in the context of their applications."

"We're in the golden age of software engineering. The scope of what one engineer can build has exploded, and the unlock is agents working with real context," said Russell Kaplan, President at Cognition, the company behind Devin. "By connecting Devin to MongoDB Atlas, engineers can hand off well-scoped tasks knowing Devin is working from live application data, not stale assumptions, and spend their own time on the harder problems."

MongoDB also announced at Build Fest new capabilities that bring its benchmark-leading Voyage AI retrieval models into the operational database, including Automated Embeddings in MongoDB Atlas powered by Voyage AI, the Atlas Embedding and Reranking API, and voyage-code-4. 

Get started with these new capabilities today for free at mongodb.com/atlas.

About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries with software. MongoDB's unified database platform was built to power the next generation of applications, and MongoDB is the most widely available, globally distributed database on the market. With integrated capabilities for operational data, search, real-time analytics, and AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures. Millions of developers and more than 67,000 customers across industries—including ~75% of the Fortune 100—rely on MongoDB for their most important applications. To learn more, visit mongodb.com.

Forward-Looking Statements
This press release includes certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including new capabilities announced at MongoDB.local Build Fest 2026. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including those risks detailed under the caption "Risk Factors" and elsewhere in our Securities and Exchange Commission filings and reports. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

Contacts

Investors: [email protected]

Media: [email protected]

SOURCE MongoDB, Inc.

New Voyage AI capabilities and Search for on-premises and private cloud let enterprises build accurate, compliant AI applications to run anywhere without rewriting their applications and relying on bolt-on tools

, /PRNewswire/ -- MongoDB, Inc. (NASDAQ: MDB) today announced new capabilities at MongoDB.local Bengaluru that address the two reasons enterprise AI projects routinely stall before production: retrieval that isn't accurate enough to trust and infrastructure that can't meet compliance requirements. voyage-context-4, Hybrid Search, and Native Reranking work together to improve retrieval accuracy, with Native Reranking alone improving retrieval quality by up to 30%*. The capabilities are powered by Voyage AI models that outperform Google and Cohere on the public Retrieval Embedding Benchmark leaderboard. Search and Vector Search are now generally available for MongoDB Enterprise Advanced and Community Edition, bringing the same retrieval capabilities Atlas customers rely on to on-premises, private cloud, and local environments where regulated enterprises and startups operate. Together, these capabilities give enterprises and builders a production-ready retrieval stack that is accurate, compliant, and deployable wherever their data lives.

"The biggest barrier to enterprise AI in production and at scale isn't the LLM. It's memory, retrieval, accuracy, and compliance. Most enterprises aren't blocked by ambition. They're held back by infrastructure that wasn't designed to provide AI with trusted access to enterprise data. Bolting on more systems to solve those problems only creates more vendors, more latency, and more points of failure," said Ben Cefalo, Chief Product Officer, Core Products, MongoDB. "Whether you're running in the cloud, private cloud, or behind a firewall, MongoDB gives you the same production-grade retrieval capabilities wherever your data lives."

Voyage AI: Accuracy begins with top-ranked embedding models
Accuracy is the first bar AI has to clear for production. The second is ensuring AI works from current data, not outdated data sitting in a separate search system. Today, MongoDB launched three new capabilities, built into the database, that deliver more accurate retrieval and keep applications working from current data.

Native Reranking in MongoDB Atlas, now in public preview, is powered by Voyage AI and delivers up to a 30% boost in retrieval quality directly inside the database, eliminating a leading cause of AI project failure. It works on top of existing search results, with no external APIs, keys, or round-trips to manage. Voyage Context 4, now generally available, is a new embedding model built for long documents. It processes long documents in full context rather than isolated chunks, preserving meaning across complex enterprise content for better retrieval accuracy. It drops into existing RAG pipelines without re-architecting. Hybrid Search in MongoDB, now generally available, combines full-text and vector search in a single query inside the operational database, delivering precision retrieval without separate systems or complex query logic. Because embeddings stay up to date automatically, agents retrieve from the current state of the data rather than a stale copy. Emergent Labs is an AI-native app development platform and one of the fastest growing startups in the world. The company first tested its platform on PostgreSQL, where agents repeatedly got stuck in schema migration loops every time users refined their ideas. On MongoDB Atlas, agents create and modify data structures freely as applications evolve, and because search and embeddings live in the same database as that constantly changing data, retrieval keeps up with it.

"Our agents write code, modify data structures, and act on what they read back millions of times a day. If retrieval returns something stale or wrong, the agent builds on it, and the error compounds. MongoDB gives us the retrieval accuracy to keep agents working from the current state of the data, and that's what lets us run two million applications at scale," said Mukund Jha, CEO of Emergent Labs.

Run AI anywhere without compromising on accuracy or increasing risk
Retrieval accuracy is only half the problem enterprises face. The other half is whether they're allowed to run it where their data must reside, and for enterprises in regulated industries, the answer is rarely the public cloud. Data residency mandates, sovereignty rules, and compliance frameworks don't bend for innovation timelines, yet the most capable AI tooling has been built cloud-first, leaving regulated enterprises to choose between compliance and capability.

Today, MongoDB Search and Vector Search are now generally available as an add-on for MongoDB Enterprise Advanced, bringing the same retrieval capabilities MongoDB Atlas customers have been building in on-premises, private cloud, and hybrid environments, with the same platform, API, and technical skills regardless of where the workload runs. Ahead of this release, more than 20 of the world's largest banks and financial institutions have been evaluating Search for Enterprise Advanced, drawn by the same thing: AI-ready retrieval that runs inside the infrastructure they control.

Search and Vector Search are now generally available for MongoDB Community Edition, enabling builders to implement AI retrieval locally at no cost. A startup can prototype on a laptop with full-text search, vector search, and hybrid search in one single system, then move to Atlas or Enterprise Advanced when it's ready to scale, without re-architecting or switching databases.

Investing in India for the long term

As part of MongoDB.local Bengaluru, the company also announced plans to upskill two million Indian builders by 2030. MongoDB is expanding its MongoDB for Academia program through partnerships with the All India Council for Technical Education, HCL GUVI, and the ICT Academy of Kerala. Since 2023, the program has reached more than 650,000 students.

MongoDB also launched Bengaluru to the Bay, a startup challenge that gives early-stage AI founders a path from India's builder ecosystem to San Francisco's AI community during SF Tech Week experience. $50,000 in MongoDB Atlas credits, travel, and go-to-market opportunities included.

What's new at MongoDB.local Bengaluru 2026

voyage-context-4 (Generally available): Next-generation contextualized embeddings with document-level context and auto-chunking; a drop-in upgrade for existing retrieval-augmented generation (RAG) pipelines. Native Reranking in MongoDB Atlas (Public Preview): Reranking runs inside the aggregation pipeline - no external APIs, no round-trips - and delivers up to a 30% boost in retrieval quality directly inside the database. Hybrid Search (Generally available): More accurate retrieval by combining full-text precision and vector-based semantic understanding in a single query on live operational data. Search and Vector Search for MongoDB Enterprise Advanced (Generally available): Production AI behind your firewall, under your compliance framework, with full parity to MongoDB Atlas capabilities. Search and Vector Search in MongoDB Community Edition (Generally available): Full-text, vector, and hybrid retrieval in self-managed environments, at zero cost to start. MongoDB Atlas Stream Processing: Apache Iceberg Support (Generally available): MongoDB Atlas now supports Apache Iceberg via the new $iceberg aggregation stage in Atlas Stream Processing, enabling any Atlas collection to be continuously synchronized to Iceberg tables on AWS object storage. Gen2 MongoDB Atlas M30+ Dedicated Clusters on AWS (Generally available): Next-generation infrastructure for high-scale production workloads. Asymmetric Search Node deployment for multi-region Atlas clusters: (Generally available): Set Search Node capacity to match each region's actual search traffic and lower total Search Node cost on multi-region clusters by 25–40%+ MongoDB for Academia Expansion: Targeting 2 million builders trained by 2030 through HCL GUVI, ICT Academy of Kerala, and AICTE partnerships. Bengaluru Meets the Bay—startup contest: $50K in MongoDB credits plus travel and VIP access to MongoDB.local San Francisco for winning founders. *Based on Voyage instruction-following rerankers on the MAIR benchmark; improvement measured over first-stage retrieval.

About MongoDB
Headquartered in New York, MongoDB's mission is to empower innovators to create, transform, and disrupt industries with software. MongoDB's unified database platform was built to power the next generation of applications, and MongoDB is the most widely available, globally distributed database on the market. With integrated capabilities for operational data, search, real-time analytics, and AI-powered data retrieval, MongoDB helps organizations everywhere move faster, innovate more efficiently, and simplify complex architectures. Millions of developers and more than 65,200+ customers across industries—including ~75% of the Fortune 100—rely on MongoDB for their most important applications. To learn more, visit mongodb.com.

Forward-Looking Statements
This press release includes certain "forward-looking statements" within the meaning of Section 27A of the Securities Act of 1933, as amended, or the Securities Act, and Section 21E of the Securities Exchange Act of 1934, as amended, including new capabilities announced at MongoDB .local Bengaluru 2026. These forward-looking statements include, but are not limited to, plans, objectives, expectations and intentions and other statements contained in this press release that are not historical facts and statements identified by words such as "anticipate," "believe," "continue," "could," "estimate," "expect," "intend," "may," "plan," "project," "will," "would" or the negative or plural of these words or similar expressions or variations. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Although we believe that our plans, intentions, expectations, strategies and prospects as reflected in or suggested by those forward-looking statements are reasonable, we can give no assurance that the plans, intentions, expectations or strategies will be attained or achieved. Furthermore, actual results may differ materially from those described in the forward-looking statements and are subject to a variety of assumptions, uncertainties, risks and factors that are beyond our control including, without limitation: our customers renewing their subscriptions with us and expanding their usage of software and related services; global political changes; the effects of the ongoing military conflicts between Russia and Ukraine and Israel and Hamas and recent events in Venezuela on our business and future operating results; economic downturns and/or the effects of rising interest rates, inflation and volatility in the global economy and financial markets on our business and future operating results; our potential failure to meet publicly announced guidance or other expectations about our business and future operating results; reputational harm or other adverse consequences resulting from use of AI and ML in our product offerings and internal operations if they don't produce the desired benefits; our limited operating history; our history of losses; our potential failure to repurchase shares of our common stock at favorable prices, if at all; failure of our platform to satisfy customer demands; the effects of increased competition; our investments in new products and our ability to introduce new features, services or enhancements, including AI and ML; social, ethical and security issues relating to the use of new and evolving technologies, such as artificial intelligence, in our offerings or partnerships; our ability to effectively expand our sales and marketing organization; our ability to continue to build and maintain credibility with the developer community; our ability to add new customers or increase sales to our existing customers; our ability to maintain, protect, enforce and enhance our intellectual property; our ability to continue to increase revenue from our Atlas platform; the effects of social, ethical and regulatory issues relating to the use of new and evolving technologies, such as AI and ML, in our offerings or partnerships; the growth and expansion of the market for database products and our ability to penetrate that market; our ability to maintain the security of our software and adequately address privacy concerns; our ability to manage our growth effectively and successfully recruit and retain additional highly-qualified personnel; our ability to integrate acquisitions and work with our strategic partners effectively; and the price volatility of our common stock. These and other risks and uncertainties are more fully described in our filings with the Securities and Exchange Commission ("SEC"), including under the caption "Risk Factors" in our Annual Report on Form 10-Q for the quarter ended April 30, 2026, filed with the SEC on May 29, 2026. Additional information will be made available in other filings and reports that we may file from time to time with the SEC. Except as required by law, we undertake no duty or obligation to update any forward-looking statements contained in this release as a result of new information, future events, changes in expectations or otherwise.

Contacts
Investors
[email protected] 

Media
[email protected]

SOURCE MongoDB, Inc.