Envestnet Asset Management Inc. Acquires 39,311 Shares of MongoDB, Inc. (NASDAQ:MDB)

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Envestnet Asset Management Inc. lifted its holdings in shares of MongoDB, Inc. (NASDAQ:MDBFree Report) by 44.6% during the 1st quarter, according to the company in its most recent filing with the SEC. The fund owned 127,425 shares of the company’s stock after purchasing an additional 39,311 shares during the period. Envestnet Asset Management Inc. owned about 0.16% of MongoDB worth $22,350,000 as of its most recent filing with the SEC.

Several other institutional investors and hedge funds also recently made changes to their positions in the business. Norges Bank bought a new position in shares of MongoDB during the 4th quarter valued at about $189,584,000. Marshall Wace LLP bought a new position in shares of MongoDB during the fourth quarter valued at approximately $110,356,000. D1 Capital Partners L.P. acquired a new stake in MongoDB in the fourth quarter valued at approximately $76,129,000. Franklin Resources Inc. raised its holdings in shares of MongoDB by 9.7% in the fourth quarter. Franklin Resources Inc. now owns 2,054,888 shares of the company’s stock worth $478,398,000 after buying an additional 181,962 shares during the last quarter. Finally, Pictet Asset Management Holding SA raised its holdings in shares of MongoDB by 69.1% during the fourth quarter. Pictet Asset Management Holding SA now owns 356,964 shares of the company’s stock worth $83,105,000 after purchasing an additional 145,854 shares during the last quarter. Institutional investors own 89.29% of the company’s stock.

MongoDB Trading Up 3.5%

Shares of MongoDB stock opened at $208.66 on Wednesday. The company has a market capitalization of $17.05 billion, a PE ratio of -183.04 and a beta of 1.41. MongoDB, Inc. has a 12 month low of $140.78 and a 12 month high of $370.00. The stock’s fifty day simple moving average is $200.37 and its 200 day simple moving average is $213.39.

MongoDB (NASDAQ:MDBGet Free Report) last released its quarterly earnings results on Wednesday, June 4th. The company reported $1.00 earnings per share (EPS) for the quarter, beating the consensus estimate of $0.65 by $0.35. MongoDB had a negative return on equity of 3.16% and a negative net margin of 4.09%. The firm had revenue of $549.01 million for the quarter, compared to the consensus estimate of $527.49 million. During the same quarter last year, the business posted $0.51 EPS. The company’s revenue for the quarter was up 21.8% on a year-over-year basis. Analysts predict that MongoDB, Inc. will post -1.78 EPS for the current fiscal year.

Analyst Upgrades and Downgrades

A number of research firms recently weighed in on MDB. Guggenheim boosted their price target on shares of MongoDB from $235.00 to $260.00 and gave the stock a “buy” rating in a research report on Thursday, June 5th. Piper Sandler boosted their target price on shares of MongoDB from $200.00 to $275.00 and gave the company an “overweight” rating in a report on Thursday, June 5th. Cantor Fitzgerald boosted their target price on shares of MongoDB from $252.00 to $271.00 and gave the company an “overweight” rating in a report on Thursday, June 5th. Morgan Stanley decreased their target price on shares of MongoDB from $315.00 to $235.00 and set an “overweight” rating on the stock in a report on Wednesday, April 16th. Finally, Bank of America boosted their target price on shares of MongoDB from $215.00 to $275.00 and gave the company a “buy” rating in a report on Thursday, June 5th. Eight analysts have rated the stock with a hold rating, twenty-six have issued a buy rating and one has issued a strong buy rating to the company’s stock. According to MarketBeat, the stock has an average rating of “Moderate Buy” and a consensus price target of $282.39.

Read Our Latest Stock Analysis on MongoDB

Insider Buying and Selling

In other news, Director Dwight A. Merriman sold 2,000 shares of the business’s stock in a transaction that occurred on Thursday, June 5th. The stock was sold at an average price of $234.00, for a total transaction of $468,000.00. Following the completion of the sale, the director owned 1,107,006 shares in the company, valued at $259,039,404. The trade was a 0.18% decrease in their ownership of the stock. The sale was disclosed in a legal filing with the SEC, which is available at this hyperlink. Also, CEO Dev Ittycheria sold 25,005 shares of the business’s stock in a transaction that occurred on Thursday, June 5th. The stock was sold at an average price of $234.00, for a total value of $5,851,170.00. Following the sale, the chief executive officer owned 256,974 shares of the company’s stock, valued at approximately $60,131,916. This represents a 8.87% decrease in their position. The disclosure for this sale can be found here. Over the last 90 days, insiders sold 32,746 shares of company stock worth $7,500,196. Company insiders own 3.10% of the company’s stock.

About MongoDB

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MongoDB, Inc, together with its subsidiaries, provides general purpose database platform worldwide. The company provides MongoDB Atlas, a hosted multi-cloud database-as-a-service solution; MongoDB Enterprise Advanced, a commercial database server for enterprise customers to run in the cloud, on-premises, or in a hybrid environment; and Community Server, a free-to-download version of its database, which includes the functionality that developers need to get started with MongoDB.

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Institutional Ownership by Quarter for MongoDB (NASDAQ:MDB)

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MongoDB Trading Volume Surges 52.46% to $459 Million Ranking 215th in Daily Volume

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On July 15, 2025, MongoDB’s trading volume reached $459 million, marking a 52.46% increase from the previous day. This surge placed MongoDB at the 215th position in terms of trading volume for the day. MongoDB (MDB) shares rose by 3.54%.

Sumitomo Mitsui Trust Group Inc. increased its holdings in MongoDB, Inc. (NASDAQ: MDB), while Mirae Asset Global Investments Co. sold some of its shares in the company.

MongoDB’s recent surge is driven by a combination of factors, including the growing demand for AI-powered applications and the company’s cloud-first strategy, which is gaining traction against legacy rivals.

Brown Advisory Inc. significantly boosted its stake in MongoDB, Inc. (NASDAQ: MDB) by 671.1% in the first quarter, indicating strong institutional interest in the company.

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How M-DAQ is using AI to speed up compliance | Frontier Enterprise

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Just like a railway switch guides trains onto the right track, M-DAQ’s AI platform automates onboarding and compliance paths.

Manual processes in the fintech space are like paying for digital transactions using cash. Because of tight regulation, fintech companies walk a tightrope when it comes to internal processes. However, that doesn’t mean technology cannot lend a helping hand.

M-DAQ Global, a fintech group specialising in forex and cross-border payment solutions, previously wrestled with a series of manual processes that significantly delayed operations. It eventually turned to AI to build an internal automation platform called CheckGPT, powered by MongoDB Atlas. Andrew Marchen, General Manager of Payments at M-DAQ Global, and Wei You Pan, Global Director of Financial Services Industry Solutions at MongoDB, spoke to Frontier Enterprise about the development and impact of the platform.

Navigating roadblocks

To meet anti-money laundering (AML) regulations, M-DAQ traditionally relied on manual background checks, document reviews, and customer onboarding. These tasks were not only time-consuming, but also inefficient, given the unstructured and sensitive nature of the data involved.

As the business scaled, M-DAQ began handling an increasing number of onboarding requests from clients in multiple jurisdictions.

“Adding personnel wasn’t a sustainable solution. Not only did it slow down our response times, but it also introduced inconsistencies due to varying interpretations of internal compliance policies by different team members. This created friction for our customers and posed a risk to our business,” Marchen observed.

The company also struggled to respond to compliance signals in real time due to fragmented data and workflows.

“Much of our AML work, particularly during onboarding, relied on fragmented systems and required extensive manual verification across multiple sources, slowing down decision-making and introducing the risk of human error,” he said.

Because the data arrived in varied formats, extracting meaningful insights often required manual cross-referencing across multiple systems, Marchen added.

Unlocking solutions

To address these challenges, M-DAQ developed an AI-powered know-your-business (KYB) platform called CheckGPT, using MongoDB Atlas as its back end.

Andrew Marchen, General Manager of Payments, M-DAQ Global. Image courtesy of M-DAQ Global.

“By automating and standardising how we assess and process customer information, CheckGPT enables our customers to access our services more quickly, without compromising compliance integrity,” Marchen explained.

The decision to use MongoDB Atlas was influenced by its flexible document model, which can handle the changing nature of compliance data, including onboarding documents and the rules-based processes they support.

But like any complex deployment, rolling out CheckGPT came with its share of growing pains.

“One of the toughest parts was building a secure system that could handle multiple clients, manage unstructured data, and deliver AI results in real time. We had to make sure each client’s sensitive data stayed completely separate, without slowing things down, and still support quick searches across different data types,” Marchen said.

To resolve this, M-DAQ adopted a database-per-tenant strategy using MongoDB Atlas, giving each client a dedicated environment to prevent data co-mingling and meet regulatory requirements.

“This architecture also made it easier to apply client-specific compliance policies and updates without system-wide disruption,” Marchen added.

According to Wei, supporting M-DAQ’s platform meant addressing two key requirements: strict data isolation for each client and the ability to manage diverse, evolving data formats at scale.

“Because the platform needed to support multiple clients simultaneously, we had to design for strict data isolation to ensure that sensitive customer information didn’t mingle with others. In regulated sectors, that level of separation is critical for compliance,” he explained.

CheckGPT processes a wide range of inputs, from onboarding forms to media reports, which often arrive in unstructured or semi-structured formats. Wei noted that the platform’s schema design made it possible to accommodate new data types over time, which supported ongoing changes to compliance workflows.

Reaping the rewards

Following CheckGPT’s launch, M-DAQ accelerated its onboarding processes, particularly for clients in highly regulated industries. By automating compliance tasks such as customer due diligence, name screening, and media checks, the platform eliminated much of the manual work that previously slowed operations.

Marchen shared the experience of a payments provider that had faced long onboarding times due to manual document handling and frequent false positives during screening.

“With CheckGPT, we now use AI to review customer due diligence documents, score risk levels automatically, and cut down on false alerts. That’s helped us reduce onboarding time by up to 80%, cut false positives by 90%, and let our teams focus on the cases that really matter,” he said.

In the six months following the rollout, M-DAQ was able to onboard 30 times more customers and scale its gross transacted value by a factor of 10, while maintaining compliance standards.

Planning for the future

Looking ahead, M-DAQ plans to evolve CheckGPT into a broader intelligent compliance and onboarding platform that supports secure cross-border transactions. According to Marchen, AI will remain central to this strategy, not only to automate workflows, but also to identify risk signals, adapt to changing regulations, and build trust across its payments ecosystem.

Wei You Pan, Global Director of Financial Services Industry Solutions, MongoDB. Image courtesy of MongoDB.

“Now that onboarding is faster and can support more clients, the next step is to use AI for transaction screening and monitoring. This will help us keep up with growth without depending too much on manual checks,” he said.

Marchen also sees opportunities to apply automation more broadly across M-DAQ’s internal operations.

“There are plenty of internal areas where automation can make a difference, from managing workflows and handling exceptions to supporting teams behind the scenes. These improvements help us work more efficiently and focus on what matters to our customers,” he said.

Using MongoDB Atlas, M-DAQ also plans to expand CheckGPT’s capabilities to support more complex, jurisdiction-specific use cases, particularly in markets where compliance rules change quickly.

Wei noted that many fintechs in Asia-Pacific are now building compliance platforms with modular, cloud-based designs that can support real-time onboarding and AML processes.

“One priority is being able to work with different types of data — whether it’s structured, semi-structured, or unstructured. That includes scanned documents, free-text notes, and even audio or video files, all of which play a role in KYC and AML,” he said.

To support these needs, Wei added, fintechs are turning to document-based data models that can adapt to various formats and power analytics across different data types, from text and time series to network relationships and location data.

Machine learning and generative AI are also playing a bigger role. These tools are now being used to build more complete risk profiles, spot issues as they happen, summarise cases, and simplify reporting requirements.

“Architectures that support scale, control where data is stored, and manage who can access what are becoming more common,” Wei said. “They help companies stay on top of evolving regulations and respond more quickly to potential financial crime.”

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MongoDB Surges 4.5%—What’s Fueling the Rally? – AInvest

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MongoDB (MDB) soars to 210.59, up 4.49% intraday, hitting a session high of 212.40
• Recent insider sales totaling $7M contrast with AI-driven Atlas platform growth and analyst optimism
• Outperforms Oracle (ORCL) by 11% YTD amid cloud-native database rivalry
• Technicals show price near 30-day resistance (208.57–209.30), with Bollinger Bands suggesting volatility expansion

Today’s surge reflects a tug-of-war between insider skepticism and AI momentum, with MongoDB’s cloud-first strategy gaining traction against legacy rivals.

AI Adoption and Atlas Growth Ignite Momentum
MongoDB’s rally stems from its AI-ready platform’s accelerating adoption. Recent Zacks analysis highlights Atlas’s 26% Y/Y revenue growth and Voyage AI’s 80% storage efficiency gains, which are critical for developers building large-scale AI applications. The company’s partnership with Campfire—a $35M-funded AI ERP startup—further underscores MongoDB’s leadership in AI-native infrastructure. Despite insider selling, analysts at William Blair and Wolfe Research remain bullish, citing MongoDB’s 72% Atlas revenue contribution and FedRAMP compliance efforts for government cloud adoption. This blend of technical execution and strategic partnerships has overshadowed short-term profit concerns.

Database Rivalry Heats Up as MDB Outpaces ORCL
While Oracle (ORCL) reports 31% cloud database growth, its reliance on legacy on-premise licensing and multicloud complexity leaves it trailing MongoDB’s pure-play cloud model. MDB’s 6.76X forward P/S ratio versus ORCL’s 9.46X suggests investors favor its nimble innovation over Oracle’s capital-heavy expansion. The 11% YTD underperformance versus ORCL’s 38.9% gain signals a sector reset: investors are pricing in MongoDB’s AI differentiation while penalizing Oracle’s slow migration from outdated architectures. This divergence validates MongoDB’s ‘Buy’ rating versus ORCL’s ‘Hold’.

Bullish Momentum Calls and Technical Breakouts to Watch
Technical Indicators:
– 200-day MA: 236.99 (well above current price)
– RSI: 48.3 (neutral, below overbought 70)
– MACD: 2.08 vs Signal 3.42 (bullish crossover imminent)
– Bollinger Bands: Near upper resistance (214.90) offers 4% upside potential

Bulls should target a breakout above 214.90 (upper Bollinger Band) for a move toward 2023 highs (370). Short-term support holds at 206.94 (middle band).

Top Options Picks:
1. MDB20250725C215 (Call, Strike 215)
– IV: 47.85% | Delta: 0.406 | Theta: -0.631 | Gamma: 0.022 | Turnover: 23,454
Why Buy? High liquidity and mid-range IV provide a balanced risk-reward. At a 5% price rise to 221.11, payoff would be $6.11/share with 127% premium gain.
2. MDB20250725C212.5 (Call, Strike 212.5)
– IV: 48.52% | Delta: 0.463 | Theta: -0.686 | Gamma: 0.022 | Turnover: 39,820
Why Buy? Highest volume contract offers superior liquidity. A 5% move to 221.11 yields $8.61/share payoff with 155% premium upside.

Trade Hook: Aggressive bulls should target MDB20250725C212.5 into a 214.90 breakout—this contract’s 35k+ turnover ensures tight spreads ahead of the July 25 expiration.

Backtest MongoDB Stock Performance
The 4% intraday surge in MDB has historically led to positive short-to-medium-term gains. The backtest data shows that:1. 3-Day Win Rate: 50.57% of days experience a return, with an average return of 0.36%.2. 10-Day Win Rate: 48.61% of days experience a return, with an average return of 0.06%.3. 30-Day Win Rate: 49.43% of days experience a return, with an average return of 0.24%.4. Maximum Return: The maximum return during the backtest period was 0.44%, achieved on day 45 after the surge.These results suggest that while there is some volatility, MDB tends to maintain positive momentum following a significant intraday surge like the 4% increase. Investors may consider these statistics when assessing the potential for continued growth in the days following such an event. 4%”, “Backtest Period”: “2020.07.15 – 2025.07.15”}], “dataSize”: 1}}], “lowcode_type”: “shunda”, “interface_request_list”: [], “lowcode_json”: {“stack”: false, “visible”: true, “childLimit”: 9999, “label”: “root”, “type”: “thslc/thslc-common-container”, “leaf”: false, “animate”: [], “version”: “1.0.1”, “script”: [], “props”: [], “path”: “//cdn.ainvest.com/frontResources/s/kernel-thslc-resource/resource/ainvest/0Ae514cfA4/js/_thslc-common-container_1.0.1_index.js”, “style”: {“background-color”: “”, “box-shadow”: “0px 0px 0px”, “color”: “”, “width”: “auto”, “min-height”: “100%”, “position”: “relative”, “height”: “auto”}, “isMaterial”: false, “id”: “root”, “needTheme”: false, “hasEditor”: false, “packed”: false, “events”: [], “child”: [{“stack”: false, “visible”: true, “customStyle”: “.backtest-results .result-tabs-container[data-v-026c0aba]{overflow:hidden;}r#thslc-canvas-wrapper .backtest-results .result-tabs-container .result-tab-item .sub-tab-select-container {r z-index: 9999!important;r}r#thslc-canvas-wrapper .backtest-results .results-chart .chart-legend .legend-item .legend-btn-chose .legend-trade{font-size: 0 !important;line-height: 12px !important;}”, “childLimit”: 0, “label”: ” “, “type”: “iwencai/stockBackTesting”, “leaf”: true, “version”: “2.2.2”, “animate”: [], “url”: “//cdn.ainvest.com/frontResources/s/foiegras/stockBackTesting/2.2.2/stockBackTesting@2.2.2index.js”, “componentUuid”: “ztxxx06c0a024223920bbbeb1e0718”, “script”: [], “props”: {“text”: “”}, “path”: “//cdn.ainvest.com/frontResources/s/foiegras/stockBackTesting/2.2.2/stockBackTesting@2.2.2index.js”, “meta”: {“js_url”: “//cdn.ainvest.com/frontResources/s/foiegras/stockBackTesting/2.2.2/stockBackTesting@2.2.2index.js”}, “style”: {“background-color”: “”, “padding”: “0”, “color”: “”, “display”: “block”, “width”: “auto”, “position”: “relative”, “height”: “auto”}, “isMaterial”: true, “_id”: 19, “id”: “iwencai/stockBackTesting0423”, “hasEditor”: true, “packed”: false, “events”: [], “isSetDefaultValue”: true}]}}, “page”: {“layout”: {“layout_data”: “[{“uuid”: “ztxxx06c0a024223920bbbeb1e0718”, “showType”: “jgyLowcode”, “children”: []}]”}, “render_for”: “aigc”, “voice_txt”: “”, “uuid”: “39189”}}”>

MongoDB’s AI Momentum Sustains—Bullish Bias Remains
MongoDB’s 4.5% surge underscores its transition from a niche database player to an AI infrastructure leader. While Oracle’s multicloud strategy struggles with legacy drag, MongoDB’s Atlas-driven growth and Campfire partnerships solidify its cloud-native advantage. Technicals favor bulls targeting 214.90 resistance, with a break spurring a rally toward 225—the next major hurdle. Investors should watch for Atlas adoption metrics and insider buying signals—absent further selling, MDB’s AI narrative remains intact. Final Alert: Hold onto long positions above 206.94; a close below 200 invalidates bullish outlook.

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MDB vs. ORCL: Which Database Stock Deserves a Place in Your Portfolio? – TradingView

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MongoDB MDB and Oracle ORCL are two leading names in the database market, but they’re built on very different foundations. MongoDB is a developer-first, cloud-native NoSQL platform optimized for flexibility and speed, while Oracle is a long-established enterprise provider known for its robust relational databases and expanding multicloud presence.

As AI adoption and cloud migrations reshape data infrastructure, the key question for investors is: Which company is better positioned to capture the next wave of growth? Let’s break down the fundamentals and financials for both MDB and ORCL to see which stock deserves a spot in your portfolio.

The Case for MDB Stock

MongoDB has been consistently gaining from the growing demand for AI-powered applications. Its flexible document model is a strong fit for handling fast-changing, unstructured data commonly used in AI. The company further strengthened its AI capabilities by acquiring Voyage AI. The latest release, Voyage 3.5, has helped improve embedding accuracy and cut storage costs by more than 80%.

The platform brings together real-time data, search and retrieval into one system, allowing developers to avoid complicated integrations. MongoDB’s tools are already in use at companies like LG Uplus, where they support thousands of agents with quicker and more accurate responses, boosting their standing in the AI space.

MongoDB has also been growing its partner ecosystem. It recently added backup integrations with Rubrik and Cohesity, improving data protection for enterprise customers, especially those using hybrid cloud setups. These partnerships highlight MongoDB’s focus on enterprise-grade reliability, adding to the momentum around the platform’s broader adoption.

In the quarter, MongoDB generated $549 million in revenues, growing 22% year over year. Atlas revenues increased 26% year over year and represented 72% of total revenues. Non-GAAP operating income was $87 million, with net income of $86 million and free cash flow of $106 million.

The Zacks Consensus Estimate for fiscal second-quarter earnings is pinned at 64 cents per share, which has remained steady over the past 30 days. The estimate indicates a year-over-year decline of 8.57%.

MongoDB, Inc. Price and Consensus

MongoDB, Inc. price-consensus-chart | MongoDB, Inc. Quote

The Case for ORCL Stock

Oracle has been expanding its cloud database business through offerings like Autonomous Database and Oracle Database 23AI. These products allow customers to run databases not only on Oracle Cloud Infrastructure but also across Azure, AWS and Google Cloud through its multicloud partnerships.

The company has focused on AI-readiness by integrating vector search into its database stack. Oracle stated that Oracle 23AI enables customer data to be accessed by large language models while preserving privacy and security. As AI adoption grows, Oracle believes its database will become increasingly central to enterprise infrastructure.

In the fourth quarter of fiscal 2025, Oracle reported that cloud database services grew 31% year over year, with Autonomous Database consumption revenues up 47%. Cloud database services were reported to have an annualized revenue run rate of $2.6 billion.

However, Oracle’s database business is under pressure as cloud migration accelerates and legacy revenue streams weaken. In fiscal 2025, database license support grew just 7%. A large portion of revenues remains tied to on-premise deployments, making Oracle vulnerable as customers shift to cloud-native alternatives. Its $21.2 billion in capital spending led to negative free cash flow of $400 million. Additionally, operating across multiple clouds adds complexity and increases reliance on rival platforms.

The Zacks Consensus Estimate for fiscal first-quarter earnings is pinned at $1.47 per share, which has remained steady over the past 30 days. The estimate indicates year-over-year growth of 5.76%.

Oracle Corporation Price and Consensus

Oracle Corporation price-consensus-chart | Oracle Corporation Quote

Valuation and Price Performance of MDB and ORCL

Valuation-wise, MDB shares are trading relatively cheaper than ORCL, although both have a Value Score of F.

In terms of forward 12-month Price/Sales, MDB shares are trading at 6.76X, below ORCL’s 9.46X.

Price/Sales (F12M)

Year to date, ORCL shares have gained 38.9%, while MDB shares have lost 11.2%. For MDB, the year-to-date plunge indicates that there is more upside left in the stock, whereas for ORCL, much of the demand and growth have already been priced in.

MDB and ORCL Stock Performance

Conclusion

MongoDB has been steadily expanding its cloud-native database platform with AI-ready features and growing enterprise adoption. While Oracle shows solid momentum in multicloud deployments, much of its growth is offset by legacy drag and capital-heavy expansion. MDB’s valuation is more attractive, and its recent underperformance leaves more room for upside. With faster product innovation, developer-led traction and improving free cash flow, MongoDB stands out as a better long-term investment in the database market.

MDB, with a Zacks Rank #2 (Buy), currently offers a better investment opportunity than ORCL, which has a Zacks Rank #3 (Hold). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.

This article originally published on Zacks Investment Research (zacks.com).

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MongoDB Inc (MDB) Shares Up 4.33% on Jul 15 – GuruFocus

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Shares of MongoDB Inc (MDB, Financial) surged 4.33% in mid-day trading on Jul 15. The stock reached an intraday high of $210.78, before settling at $210.25, up from its previous close of $201.52. This places MDB 43.18% below its 52-week high of $370.00 and 49.35% above its 52-week low of $140.78. Trading volume was 878,370 shares, 33.1% of the average daily volume of 2,653,057.

Wall Street Analysts Forecast

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Based on the one-year price targets offered by 36 analysts, the average target price for MongoDB Inc (MDB, Financial) is $279.66 with a high estimate of $520.00 and a low estimate of $170.00. The average target implies an upside of 33.01% from the current price of $210.25. More detailed estimate data can be found on the MongoDB Inc (MDB) Forecast page.

Based on the consensus recommendation from 38 brokerage firms, MongoDB Inc’s (MDB, Financial) average brokerage recommendation is currently 1.9, indicating “Outperform” status. The rating scale ranges from 1 to 5, where 1 signifies Strong Buy, and 5 denotes Sell.

Based on GuruFocus estimates, the estimated GF Value for MongoDB Inc (MDB, Financial) in one year is $379.42, suggesting a upside of 80.46% from the current price of $210.25. GF Value is GuruFocus’ estimate of the fair value that the stock should be traded at. It is calculated based on the historical multiples the stock has traded at previously, as well as past business growth and the future estimates of the business’ performance. More detailed data can be found on the MongoDB Inc (MDB) Summary page.

This article, generated by GuruFocus, is designed to provide general insights and is not tailored financial advice. Our commentary is rooted in historical data and analyst projections, utilizing an impartial methodology, and is not intended to serve as specific investment guidance. It does not formulate a recommendation to purchase or divest any stock and does not consider individual investment objectives or financial circumstances. Our objective is to deliver long-term, fundamental data-driven analysis. Be aware that our analysis might not incorporate the most recent, price-sensitive company announcements or qualitative information. GuruFocus holds no position in the stocks mentioned herein.

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Presentation: From Junior to Staff and Beyond: Lessons Learned

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Transcript

Rey: I started coding in 1999. I was 12 years old at the time. That was the first programming book that I read cover to cover. That was my first programming language (Visual Basic). It’s not very popular today, but today I have no shame in saying it. I’ve been working professionally in tech for 17 years, working since I had my first full-time job at a serious company. It took me 15 years to become a staff engineer, which is my current role at Eventbrite. You might think 15 years to become a staff engineer is a long time, and you’re right, that’s a problem. That’s hopefully what will not happen to you if you listen to this talk, and how you can help others grow faster as well.

This talk is for those who want to grow in their career, who want to climb that ladder, but it’s also for those who want to help others grow. We’re going to discuss growth, basically. We’re going to discuss the ladder. I expect most of the people to be on the second part, but there might also be some on the first part. Again, the topics are the same, so there’s really no difference.

The Plan – You Trace Your Own Path at Your Own Pace

I thought a lot about what drives growth. I also did a lot of research. I also talked to a lot of people preparing for this talk. What I came up with in order is that, the first factor, and probably the most important one, is ambition. It’s really hard to grow in your career if you don’t have that ambition. In second place, I find that capacity is important. Being able to perform, being able to learn new things, all of that. In third place, you might be very good at both. You might be excellent at your job, but you need an external factor. You need that opportunity. There’s nowhere for you to grow. It’s really hard to do that. The reason why I put ambition first instead of capacity or curiosity, or whatever, becomes really clear when you think about the definition of ambition. The one I like from the Oxford Dictionary says that ambition is a strong desire to achieve something, typically requiring determination, effort, and drive.

If you read between the lines, what this is telling you is that a person with ambition will be able to develop that capacity as needed. They will do that through determination, effort, and drive. They will learn whatever they need to learn. I want you to put yourselves, for a moment, in the shoes of a person who’s very early on their career, just starting, just accepting their new job. Probably the company offered them a position and told them, “Yes, this company is growing. You’re going to grow really fast. It’s going to be great for you”. Things don’t always go that way. Sometimes we find that the first years of our career look more like this. This is very typical. It’s not terrible, but if you want to accelerate growth, you should try to avoid this. You should start by identifying the problems. What is causing this type of growth in your career that’s not really fast because it’s not really directed?

Typically, it’s one of two things. It’s either a lack of focus on execution or a lack of direction. When we go to high school and college, they tell us that we should strive for perfection. You want to have that perfect grade. You want to have that perfect opinion from your teachers about your work. As soon as you get into business, you need to completely change your mindset. Perfection is the killer of execution. This is very well put in the Amazon Leadership Principles as bias for action. That’s one that I really like. In the early years of someone’s career, it’s very important to help them make this shift of mind, make this shift of paradigm, and to start focusing on execution over perfection, without dropping quality, of course.

Secondly, if someone is having trouble finding their direction, there are ways to help them. The best thing is for them to do research first on their own. Then, the second turn, to seek for mentoring. When I talk about research, you can read a book and you can read a blog, that’s good. You should also do your own research. If you think, I want to be a staff engineer in five years, or I want to be a manager, you should look probably within your company and ask yourself, what does a manager’s life look like? What does a staff engineer do? How do these people work? How did they get there? Is that really what I want for my life? That’s the type of research that will bring things a bit more down to earth and make them more achievable.

You should also look at blogs and books to get the theory behind that. Again, when someone is coming out of college, seeing things in the real world makes a real difference. It’s important to do that part as well.

Again, put yourself in the shoes of someone who’s early in their career and they’re having trouble growing. Typically, they ask themselves, why are we not growing? What’s happening? Many people will come up with these answers. The market is terrible right now. I miss the golden era. We all did. There’s always some nostalgia to some golden era that never existed, really. That doesn’t matter. This can be real, but they can also be seen as just excuses. There are also people who will come up with these types of responses, “I haven’t been directing my efforts efficiently, or, I have poor time management skills”. If you look at it, these ones on the right hint much more introspection and sound much more personal. The ones that I put here are real life examples from people close to me, from people I’ve mentored, and even some of my own. This is a very popular framework. Some of you might have recognized it already. This is known as the victim-player framework.

Essentially, what it says is that what you cannot control makes you weak, but what you can control makes you powerful. We have the idea, mostly when we’re young, to think about showing weaknesses is what makes me weak. In real life, it’s quite the opposite, showing your weaknesses is what makes you strong. I’m not going to go into a lot of detail on the victim-player framework. I’m going to give the quintessential example of it, which is how two different people might react to a traffic jam. One employee can say, “It’s a very big problem. It was totally unpredictable. There is nothing I can do now. I’m just stuck here”. An ideal employee would probably call their boss and tell them, “Boss, I’m sorry. I had a big problem today. I’m at a traffic jam. I’m going to have to take the first call from my car. I hope that’s not a problem. I can stay up and make some extra time today if necessary.

Also, I’ve realized that this is a recurring pattern, and I’ve already made a decision to start taking the train instead, because it’s becoming unacceptable”. This is someone taking ownership of that situation. Of course, this is a very typical example, but in real life, you know how it goes. This is also very similar to other concepts. They’re all the same thing. It’s also called being proactive or taking agency, not being the victim. It’s the same thing. It changes over time. The concepts are slightly different, but they’re all aimed at taking control of what you can, essentially.

I mentioned I included a couple of my own here. Today, I have no shame in saying that. I’m not ashamed of my first programming language, which you already know. I started working when I was 20. Early on in my career, I noticed that I was having issues with my work. Mostly, it was very hard for me to have a meeting with people outside of my company because my social anxiety was terrible. It’s really hard for me to speak publicly here today. Also, I couldn’t execute anything over a long period of time.

Obviously, I was job hopping a lot, which is sometimes normal in the early stage of your career. When I was 23, I was doing a lot of introspection, and I had the good luck of having a great manager at the time who provided me with a safe place where I could feel confident talking to him. It took me a lot of time. I didn’t have the tools at the time to identify this. It took me three years. When I did, I came up to him one day and told him, “I think my depression is setting me back”. He told me, “Yes”. However, his response was great.

After that, we came up with a plan together. He spent months working with me in order for me to get better. I’m better today. He continued to make sure that I felt safe at work and that there wouldn’t be any retaliation or anything. He took care of the projects. He paired me with some other people and everything. He was a great guy, Gustavo. Shortly after this, there was a meeting at a bar with work colleagues. Someone else got a promotion. Of course, I didn’t because I was doing terrible. This was back in the day when we worked at offices and we had to wear suits and everything. This was a very traditional company. This person had bought a new suit and came to the bar. Someone told him, you look great. Someone else said, a man who takes care of himself is a man who can take care of others.

That phrase at that time really resonated with me because that’s when it hit me, like, how am I expected to lead a team if I cannot put my own life back together? I talked about that a lot with my boss at the time. I got my shit together, basically.

That started working better. If you think about my manager’s reaction at the time and why he helped me, it wasn’t just because he’s a great guy, which he is. It was also in the best interest of the company. When people don’t grow, many people will blame their company for their bad career path. They will say, the company is holding me back and things like that. Truth is, companies usually don’t do that. It’s very rare for a company to do that. It’s in the best interest of a company for their employees to do well, to thrive. They will help you.

Companies don’t want to deal with low-performing employees. Companies don’t want to put you on a performance improvement plan or anything like that. It’s very expensive for the company to do that. It’s more profitable to have employees who are doing well. Managers are expected to help them do well in order to achieve that, in order to have a well-functioning team that starts providing value, at a good pace.

Once I made that click, that’s when my career really took off. That’s when I really started growing. I had good mentoring. I was lucky to have that. The best advice I got was to keep it at your own pace and keep it consistent.

A very typical example for this is comparing the workplace to physical exercise. It’s easy to go out running for 10 minutes. Most people can do that. It’s really hard to do that consistently two or three times a week, or once a day for one year, two years, or five years. Will you go out every day? Will you go out even when you have a congestion? Experts say that it’s totally fine. Will you go out even on the cold days, when it’s raining, when it’s snowing? I don’t run as much. I cycle a lot. That day was cold, my friends. I can tell you that. This sounds very obvious when we talk about exercise.

For many people, it’s not so obvious when we talk about our professional career, and it should be. It should be just the same. It’s really obvious when you really think about it. When you plan for your career growth, you should acknowledge that you will have highs and lows, and that you will have good days and bad days. That your ambition is important only up to a level, and you should not overdo it.

I talked a lot about me during the time from the perspective of someone who is growing. From the perspective of a manager or a leader who’s helping someone, we should also identify that. That person who tries to run a marathon on day one. That person who attempts to lift 100 pounds on day one. That’s totally impossible, of course. In the work environment, it’s sometimes quite obvious as well. Think about that person who only cares about the title specifically or their salary.

That person who doesn’t care about the project, doesn’t care about the company. Especially the person who doesn’t care about the team, who doesn’t empathize with the human beings around them. That person is a ticking time bomb to any team. They might be good in the short term, they might put out good work or whatever, but that will be very bad for your team and for the company in the longer term. There’s a great talk on this topic by Simon Sinek called, “Performance vs Trust”. The way he puts it basically, if you put trust in one axis and performance on the other one, performance being how much work they output and trust being how much trust they inspire to their colleagues, to their teammates, of course, nobody wants these folks, and of course, everybody wants these ones.

The way he frames it is that you should choose always people from this category over people from this category. It sounds obvious, but sadly in the workspace, it’s not so obvious all the time. There’s a reason. He goes on to saying that promotion cycles typically tend to favor these individuals. The reason for that being that promotion cycles should be objective and they should be based on real hard data. It’s easy to measure performance, but it’s really hard to measure trust. How much trust does a colleague inspire? How much do they empower their team to be better just by feeling safe? It’s hard to do that. This was called out on the keynote by Lizzie. TAPPs is one framework to do that, there are many others. It’s one way to measure it.

The truth is, this can be measured and this can be measured as well. It’s not impossible. It’s more costly and you should do that investment in order to find these folks. The people from this category can be grown into being here in the short-term or in the mid-term. If you find someone here, it’s almost impossible to get them here. That was also mentioned by Charlotte. It’s really hard to change the character of a person. You can change their capacity. You can help them grow. You can teach them things, but you cannot change who they are.

Growth Strategies

We’re going to talk about a few more concrete growth strategies. The first thing I’d like to mention for this is that, any employee attempting to grow should understand the roles and expectations of their company. There’s a lot of resources online to do this. Levels.fyi is a great page. There are public career ladders that you can look up. Eventbrite has given me the permission to make our own career ladder public for the purpose of this talk. You can look it up later. There will be links at the end. I’m not going to go through the career ladders here. It’s a very big topic. If you’re interested in growing, please do your research. There’s a lot of interesting resources on this topic.

On strategies, I think one of the most important ones is to keep perspective in mind. When you’re working on your day-to-day, you should be asking yourself, what is best for me? What is best for my team? What is best for our customers? Also, what is best for my company? This is ambitious for someone who’s just starting on their career. They’re not going to change their company on day one, of course, but having that perspective is important, understanding how their work connects to their company goals. You should also ask, how and why? How does my company’s business model operate? Why is my team focusing on this project in this quarter? Things like that. Why am I being asked to prioritize this task over this other one, which I feel is more important? If you have that ambitious perspective, if you understand your leaders, you will be able to grow faster in your career. This was also mentioned by Dan, on aligning your goals with your leaders’ goals.

Another strategy, of course, is to find your role models. This is probably the most popular ones. There should always be people you look up to, people you admire. You should try to work with them. Maybe observe how they work. See what they do that you cannot do as well yet. You can approach them and ask them how they learned it, how they built the skill, and how you can build it. They might recommend that you read a book or that you pick up a habit. Maybe you can just ask them to mentor you. Ideally, these are people inside your company, but they can also be people from outside as well.

Another thing you should do, of course, is to identify your strengths and weaknesses. We all have strengths and weaknesses. We should do that introspection to try to identify them, but that should always be validated externally because we all have blind spots. That external input is super valuable. As mentors, as leaders, we should make sure that those are clear as well. We should have those uncomfortable conversations with someone. Tell them, your tickets are terrible, you never put enough information. Or, you’re not testing your changes and the team has to cover you all the time with tests. Things like that. Sometimes people don’t do this knowingly because they’re lazy. Or sometimes they’re just not aware of it because it’s one of their blind spots.

If you don’t discuss it with them, it’s quite unfair to judge them on it. You should make sure that those are clear and discussed always. Of course, you don’t have to be good at everything. I really like this type of chart. This was made popular by soccer, particularly soccer video games. It’s great at showing how different people have different strengths and weaknesses, and they all come together to form a team that does well. In this case, they don’t play together. That’s not the point. That’s actual feedback given to me in 2020. I remember really being appreciative of the manager who gave me this feedback. It was so visible, so tangible. Like saying, “You’re having great productive impact. Your throughput is awesome, but you’re doing a lot of rework. You need to work on that. You need to improve that so that I can promote you”. This type of feedback is really valuable. As we grow in our career also, things like the playground opens a bit and things become more vague. This was mentioned in the ambiguous role of a principal as well.

As a staff, you can choose where you want to put your effort. You can choose to be an architect, but you don’t really need to choose only one archetype, as he phrases it. You can choose to be the solver who sometimes acts as a tech lead, or you can shift your time 50-50 between being a tech lead and the right hand. Those are all valuable. There are no rules on how to act. You should find your own place by finding your strengths and finding what your team needs and what your company needs, and how you can apply those strengths.

On the next topic, you should always know yourself and acknowledge that you will have highs and lows. Nobody is perfect. It’s important that even at your lows, you find ways in which you can stay productive and in which you can stay valuable to your team and to the company. Coming back to strengths and weaknesses, it’s important to act on improving your weaknesses, but also, you should maximize your strengths. If you focus on what you’re strong in, what comes naturally to you, that’s what you should do when you’re going through a low. “This work is easy for me, I’m going to focus on this while I’m here, because that’s how I can be valuable to the team. Once I’m better, I’m going to focus on fixing my weaknesses and everything, and that’ll be ok. Right now, I’m going to focus on what’s easy”. You should discuss it with your manager, of course, to make sure that he’s aligned. You should be open if you’re going through a low.

Another thing is what energizes you and what drains you. A typical example is social interactions. Human beings are social beings by nature. We need that oxytocin. We need that serotonin. Different brains need them at different levels. Some people get them at work, and some people don’t. Some people, when they go through a technical topic, a really difficult challenge, they need to discuss that challenge with someone else. After discussing it, they come out energized off the meeting and are more productive for the following hours. A bunch of other people come out of the meeting totally drained and need some time to recuperate. That’s perfectly fine.

Another example is how people act under pressure. Typically, this is during incidents. I am the type of person that’s energized by an incident. I’m fueled by it. I love the team that comes together, the strong dedication and collaboration. Some people just loathe it. They don’t like working under pressure, and they like to pace their work more slowly. As a recent example, a short time ago, me and a colleague, another staff engineer, we were both transferred from one team to another. That basically creates a lull. The whole team starts forming, storming, norming, performing again, and we were both out of our domain. We didn’t know what we were doing, basically.

The other guy goes to our manager and says, “I’m going to take it slow. I’m going to take my time to learn. I’m not going to be productive during the time that I’m learning, but that’s going to make me more productive in the future, and I think it’s a good investment”. The manager says, “That’s great. Thank you”. I come up to the manager and I tell him, “I need that feedback. I need this action. I’m going to take the on-call for a while. Let me deal with the incidents. That’s how I can be valuable to the team fast. That’s how I can provide value with what I know. Also, that’s a way for me to learn fast”. The manager says, “That’s perfect. Thank you”. He was very appreciative that we were both open about our strengths and weaknesses and that we found ways in which to apply them to the team. Two different persons, two different approaches, both were perfectly valid, the right one for each person.

Let’s talk a bit about opportunities. It’s very important to recognize opportunities and to know how to act on them. The typical opportunity, the ideal one, like the Holy Grail, is company growth. Of course, if a company is growing, they will shape up new teams. There will be opportunity for you to grow within them.

Another opportunity is an open position above you. If a tech lead or a manager leaves the team or leaves a company, that position is open, and you can offer yourself to fill it. That’s sometimes a double-blade sword because there’s typically a reason why they left the company. You should make sure that whichever challenges they were facing at the time are challenges that you can deal with better than them, if those were the reasons why he left. It’s typically good to discuss that with the person who’s leaving instead of with the people who remain around you. Another opportunity is challenging times. This is the most difficult one, maybe. A lot of companies have been through layoffs lately, and that can create opportunity for growth, even as challenging as it is. There is the concept of anti-fragile.

The typical example is in the film Superman vs. Batman, where we have Doomsday: each time you hit him, he becomes stronger. A flower vase is fragile, if you hit it, it breaks. Doomsday, you hit him and he becomes stronger. As an employee, some people, when they get hit through going through a challenging time, they come out stronger. Those people are super valuable to a company, and it’s really hard to find them. It’s one way in which you can change a challenging time into being an opportunity.

Finally, if you don’t have opportunities, you should try to create them. You can propose initiatives for your company or for your team. You can maybe ask to be transferred to another team or choose to leave the company. Or you can do things outside of your day job, like coming to a conference, for example. This topic of creating your own opportunities was perfectly covered by Pablo, on finding your dinosaurs. I suggest you look that up as well.

Another thing you should do if you want growth is to find ways to make your work be visible. The first thing, you should always keep a track of your work. When you’re beginning your career, this might sound unnecessary, but once you’ve worked 5, 10, 15 years, it becomes really hard to remember what you were doing 2, 3 years ago. Sometimes it’s good to keep a document. Julia Evans has a great article on this. It’s called the brag document, where you brag about your own work. This is also very valuable when companies are going through change.

Typically, your manager can change, sometimes in the same year, you have two or three managers, and they lose that context of what you’ve done. It’s very hard to transfer that from one manager to another. It’s much easier for them if you provide them with a brag document, where they can track that work with a paper trail. Another thing is to publish your work. This topic was also covered by Pablo. Make sure that your contributions are seen. Aaron Francis has a great article on this, publishing your work, and how it increases your luck.

Leaders – You’ve Grown, Now What?

Finally, let’s talk about leaders for a bit. Once you’ve grown, what can you expect? When we think about staff engineers and principal engineers, one way to define them is how they can impact a large group, like broader than a team, and sometimes how they can impact an entire company. One way we typically do that is setting guidelines on how the company should work, or how the team should work, or the pillar, or whatever you call it in your company. You can work in establishing team boundaries and structures. You can work to define the software development life cycle: how we do PRs, how we do testing. Giuliano from Mercado Libre mentioned at QCon, absolute freedom is not good for companies. We should give the teams those guidelines, and we as leaders should be the ones doing that. Also, we should strive to identify when there are new patterns or new necessities. Once we have set those guidelines, something can fall through the cracks between them, and some team might choose to go on their own path.

At Eventbrite, the way we approach this is by setting a golden path. We don’t have a strict guideline on what teams can do. We give them a golden path, and we say, if you use these technologies and this software development life cycle, your life will be easy. We will take care of your problems for you. If you choose to strive out of that, you’re on your own. You’re a lone wolf. You need to take care of your own infra, your own platform, and everything. It’s not forbidden, but it’ll be more work for your team. One thing that we need to do is to maintain that. One team might be a lone wolf, but if we have two, three, four, five teams doing the same thing, it’s not lone wolves, it’s now a new pack. We need to put them back into the golden path by saying, this pattern that you’re using is now part of a golden path because we see it becoming a new necessity that our company will have.

Another thing is that when we grow to become leaders, you remember that person looking up to their leaders? Once you become this person, you are the person they look up to. Your work must not only be good anymore. Your work must be exemplary because people will look up to you. They will imitate you. They will copy how you work. Sometimes we feel that given our growth, we have great judgment, and we know when to cut corners, which changes we can push without testing, or whatever, which risks we can take, which corners we can cut. We do have that judgment, and we can make those calls, but we should be very cautious. It might be best not to make them only for the sake of being exemplary.

If you choose to do that, some people might imitate you and choose to start cutting corners at their own judgment, and their judgment might be not as good as yours. That creates a challenge for the company. It’s best if you choose to never cut corners so that you instill that way of working in your company, because it permeates into company culture without you knowing it. You should always be aware of that when you’re a leader.

Finally, and most importantly, we must stand for our peers and subordinates when we feel like they’re being treated unfairly. Sometimes, as team leads or tech leads, we see how things operate within a team, and someone from above might not have that visibility, and unfairly blame someone for something that wasn’t really their fault. It’s our job to come up to them and tell them, “You’re misunderstanding the situation. This person was not at fault here. There was a fault at the process. We should look into that instead of blaming the person”. Remember, be ambitious, stay focused, be efficient, find your opportunities, and most importantly, take care of yourselves.

Questions and Answers

Participant 1: I feel like when you grow in your career, you take on tasks which you didn’t really do when you were more junior. It’s like novel tasks. Have you seen opportunities, if you look back at your career, on how to maybe develop those skills when you don’t necessarily have a chance to put them in practice?

Rey: Yes, it’s hard. It’s good to try to jump the gun, and be ready before those necessities come. It’s good to try to develop those necessities for yourself. I think it comes back to the early part of my talk, not aim for perfection, and aim for execution instead. I will not focus on what I will need in the future, I will focus on what I need today, and start being great at that. Once you have that covered, you can start looking into that. Without having the actual necessity and without having the opportunity to apply that in a productive environment, it becomes really hard to develop that on your own.

The obvious way to do it is for tech skills, try to have some pet projects or whatever on the side that you can test new technologies or whatever. I wouldn’t put too much effort into developing something that you might or might not need. If you were to do that, I would frame it like looking at your role models and looking at how they work. Because you can confirm that those are skills that are actually needed in your company. How do you develop them? The best thing to do is to ask them directly how you can develop those skills.

Participant 2: As you mentioned, someone got hit, but then they got stronger. Do you think you’re that kind of person, or what traits does this person have?

Rey: I cannot tell you which kind of traits this person has. I sometimes can identify them, but I cannot put it into words yet. It’s not a skill that I have developed. I wouldn’t say that I’m that type of person all the time, but I have had opportunities where I came out stronger off a challenging situation. My whole team was let go at once and I was the only member who remained there. That was very challenging, but it was also very accelerating to my career growth. I think anybody has the capacity to do that, given the right environment. Environments, when they’re challenging, people around us can help us to mitigate that challenge and come out stronger.

Participant 3: What made you change teams and what advice would you give to someone considering that?

Rey: Sometimes it’s your choice and sometimes it isn’t. If there’s a topic that’s of your interest, you should discuss that with your managers, your leaders, and tell them, I would like to work in this team in the future. It doesn’t need to be this week, it doesn’t need to be this quarter, but I would like to aim my career in that direction. Sometimes companies go through big reorgs and it’s not your choice to end up in one team or another, but it is up to you to make the most out of it. It comes back to the big team player framework. How can I make the most out of this situation? It’s challenging because you don’t have the domain expertise, you don’t have the knowledge, but you need to acknowledge that it’s going to be a rough patch in your career where you need more time to learn, but that it can also be an opportunity if you can make this team succeed by now having you, and how you can do that.

Participant 4: When you’re just a junior engineer and you’ve been in your company for a good bit and you start to recognize some inefficiencies across the organization and the processes, do you think at that level you can already start to plan these initiatives and try to influence direction, or is that something you really have to wait for once you can achieve that level and have that influence? I’m curious on your perspective on that.

Rey: I think it really depends on the context. It’s not the same thing to do that at a company with 10,000 employees against doing that at a startup with 20 employees. If you’re a junior at a startup, you’re very well empowered to make those initiatives. Large companies tend to favor diversity of voices lately and tend to try to listen to anyone. There’s the opportunity to do that, but it’s much harder to come up with a real idea that will actually change the company if it’s so big. I think you can always do it, but it’s going to be much easier if the company is smaller.

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2 Reasons to Sell MDB and 1 Stock to Buy Instead – StockStory

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<br /> 2 Reasons to Sell MDB and 1 Stock to Buy Instead<br />

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Adam Hejl /

2025/07/15 12:06 am EDT


Over the last six months, MongoDB’s shares have sunk to $201.54, producing a disappointing 17% loss – a stark contrast to the S&P 500’s 5.4% gain. This might have investors contemplating their next move.

Is there a buying opportunity in MongoDB, or does it present a risk to your portfolio? Get the full stock story straight from our expert analysts, it’s free.

Why Is MongoDB Not Exciting?

Even with the cheaper entry price, we don’t have much confidence in MongoDB. Here are two reasons why you should be careful with MDB and a stock we’d rather own.

1. Operating Losses Sound the Alarms

While many software businesses point investors to their adjusted profits, which exclude stock-based compensation (SBC), we prefer GAAP operating margin because SBC is a legitimate expense used to attract and retain talent. This is one of the best measures of profitability because it shows how much money a company takes home after developing, marketing, and selling its products.

MongoDB’s expensive cost structure has contributed to an average operating margin of negative 8.1% over the last year. Unprofitable, high-growth software companies require extra attention because they spend heaps of money to capture market share. As seen in its fast historical revenue growth, this strategy seems to have worked so far, but it’s unclear what would happen if MongoDB reeled back its investments. Wall Street seems to be optimistic about its growth, but we have some doubts.

MongoDB Trailing 12-Month Operating Margin (GAAP)

2. Mediocre Free Cash Flow Margin Limits Reinvestment Potential

Free cash flow isn’t a prominently featured metric in company financials and earnings releases, but we think it’s telling because it accounts for all operating and capital expenses, making it tough to manipulate. Cash is king.

MongoDB has shown mediocre cash profitability over the last year, giving the company limited opportunities to return capital to shareholders. Its free cash flow margin averaged 7.6%, subpar for a software business.

MongoDB Trailing 12-Month Free Cash Flow Margin

Final Judgment

MongoDB’s business quality ultimately falls short of our standards. Following the recent decline, the stock trades at 6.9× forward price-to-sales (or $201.54 per share). Beauty is in the eye of the beholder, but we don’t really see a big opportunity at the moment. We’re pretty confident there are more exciting stocks to buy at the moment. We’d recommend looking at the most dominant software business in the world.

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Article originally posted on mongodb google news. Visit mongodb google news

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Database vendor MongoDB embraces GenAI – TechTarget

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Posted on nosqlgooglealerts. Visit nosqlgooglealerts

MongoDB awakened early to the rapid rise of generative AI and moved quickly to incorporate the new technology into its database platforms.

The vendor — whose NoSQL database is widely used in financial services, retail, media, healthcare and entertainment industries — started working on a vector search system soon after OpenAI’s groundbreaking release of ChatGPT in November 2022, according to Ben Flast, director of product management at MongoDB. Vector search is critical to building and using GenAI applications.

“We kind of got into it at the point I would say [was] the apex of some of the excitement around it,” Flast said on the Targeting AI podcast from Informa TechTarget. “And so far, it’s been amazing.”

“Fundamentally, at the end of the day, vector search’s relevance for … GenAI and large language models has been its ability to kind of provide semantic search to give the models factual information to ground their responses in,” he continued.

In recent years, MongoDB has made some other notable moves on the GenAI front.

The vendor unveiled Atlas Stream Processing a year ago to produce real-time updates of GenAI models. In May, MongoDB revealed that it has adopted the GenAI community’s first significant standard, the Model Context Protocol created by GenAI vendor Anthropic.

“With … MCP, we’ve really just doubled down on our commitment to the community around use and building applications using AI capabilities,” Flast said.

Flast, known as the “resident AI expert” at MongoDB, is enthusiastic about the potential of generative AI and its hot new offshoot, agentic AI, to improve his company’s technology.

“Agentic is very exciting. I think it’s kind of the new application pattern, if you will, of AI capabilities,” he said. “MongoDB is a database company. Our lifeblood is storing and securing and protecting and making durable your data. So we see ourselves relate to agents and agent workflows through that lens.”

Shaun Sutner is senior news director for Informa TechTarget’s information management team, driving coverage of AI, analytics and data management technologies, and big tech and federal regulation. Esther Shittu is an Informa TechTarget news writer and podcast host covering AI software and systems. Together, they host the Targeting AI podcast series.

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Google DeepMind Announces Robotics Foundation Model Gemini Robotics On-Device

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Article originally posted on InfoQ. Visit InfoQ

Google DeepMind introduced Gemini Robotics On-Device, a vision-language-action (VLA) foundation model designed to run locally on robot hardware. The model features low-latency inference and can be fine-tuned for specific tasks with as few as 50 demonstrations.

Gemini Robotics On-Device is the latest iteration of the Gemini Robotics family and the first that can be fine-tuned. It is intended for applications that need to run locally on the robot hardware for low latency or because of a lack of networking. The model follows natural language instructions and uses vision to find and reason about objects in its environment. DeepMind trained the model on dual-armed Aloha robots but also evaluated it on several other robotic platforms, showing that it could handle complex tasks on new hardware. According to DeepMind: 

Gemini Robotics On-Device marks a step forward in making powerful robotics models more accessible and adaptable — and our on-device solution will help the robotics community tackle important latency and connectivity challenges. The Gemini Robotics SDK will further accelerate innovation by allowing developers to adapt the model to their specific needs. Sign up for model and SDK access via our trusted tester program. We’re excited to see what the robotics community will build with these new tools as we continue to explore the future of bringing AI into the physical world.

DeepMind first announced the Gemini Robotics family earlier this year. Based on Google’s Gemini 2.0 LLMs, Gemini Robotics includes an output modality for physical action. Along with the models, DeepMind released several benchmarks, including the ASIMOV Benchmark for evaluating robot safety mechanisms and the Embodied Reasoning QA (ERQA) evaluation dataset for measuring visual reasoning ability.

DeepMind tested their model’s ability to adapt rapidly to new tasks. For seven different tasks, such as preparing food and playing with cards, they fine-tuned the model with at most 100 demonstrations; on average, using their model the robot successfully completed the tasks over 60% time, beating the “current, best on-device VLA.” However, the off-device version of the Gemini Robotics model performed even better at nearly 80%.

In a Hacker News discussion about Gemini Robotics On-Device, one user wrote:

I’ve spent the last few months looking into VLAs and I’m convinced that they’re gonna be a big deal, i.e. they very well might be the “chatgpt moment for robotics” that everyone’s been anticipating. Multimodal LLMs already have a ton of built-in understanding of images and text, so VLAs are just regular MMLLMs that are fine-tuned to output a specific sequence of instructions that can be fed to a robot….The neat part is that although everyone is focusing on robot arms manipulating objects at the moment, there’s no reason this method can’t be applied to any task. Want a smart lawnmower? It already understands “lawn,” “mow”, “don’t destroy toys in path” etc, just needs a finetune on how to correctly operate a lawnmower.

Gemini Robotics On-Device is not generally available but interested developers can sign up for the waitlist. There is also an interactive demo of a related model, Gemini Robotics-ER, available on the web. The Gemini Robotics SDK is available on GitHub.

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