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In October 2024, three senior government digital leaders made their way to Amazon’s London HQ for a panel discussion on “rewiring Whitehall” organised by the Department for Work and Pensions’ digital team.

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Zepto, the quick commerce giant, leverages MongoDB Atlas to overcome significant scalability challenges. “Behind Zepto’s 10-minute delivery promise is a database built for speed!” said Sachin Chawla, VP for India & South Asia at MongoDB, in a recent social media post. 

By shifting from a monolithic architecture with relational databases to MongoDB’s NoSQL platform, Zepto reduced latency for its critical APIs by 40%. This change also boosted its ability to handle six times more traffic, improving both operational efficiency and the overall customer experience.

The Challenge: Scaling Quick Commerce

Founded in 2021, Zepto revolutionised the Indian grocery delivery industry with its promise of 10-minute deliveries. However, as Zepto expanded—achieving $1.5 billion in annualised sales by mid-2024—its legacy infrastructure struggled to keep pace. 

Performance bottlenecks, high latency, and an inability to deliver real-time analytics hindered growth and operational efficiency.

A few months ago, during a presentation at MongoDB.local, Mayank Agarwal, senior architect at Zepto, explained: “We had a big monolith, and all the components were powered by PostgreSQL and a few Redis clusters. As our business grew, we faced many performance issues and restrictions on the velocity at which we wanted to operate.”

Zepto’s reliance on Redis clusters for caching also became a bottleneck as the business scaled. Kshitij Singh, technical lead at Zepto, noted, “We had a pretty huge Redis setup which we wanted to get rid of, as we were not able to scale it further. MongoDB’s in-memory caching solved this problem for us.”

Why MongoDB Atlas?

Zepto sought to break its monolithic architecture into microservices and migrate to a NoSQL database to address its issues. After evaluating multiple databases, MongoDB stood out due to its ability to handle nested document structures and array-based queries effectively.

“The queries were very performant, given the required indexes we had created, and that gave us confidence,” said Agarwal. “The biggest motivating factor was when we saw that MongoDB provides in-memory caching, which could address the huge Redis cluster that we couldn’t scale further.”

MongoDB’s Atlas platform also offered features such as real-time data archival and analytical nodes, enabling Zepto to separate customer-facing workloads from internal queries. Singh highlighted: “This ensured that customer performance wasn’t compromised.”

Results: Faster, Scalable, and Reliable

Zepto’s migration to MongoDB Atlas resulted in improved efficiency at an overall operational level. The company witnessed a huge reduction in latency, thereby significantly improving the response times of critical APIs and enhancing the customer experience. 

Additionally, the infrastructure scaled to handle 6x more traffic, ensuring no performance degradation. 

The migration to MongoDB also led to a 14% improvement in page load times, contributing to higher conversion rates and increased sales. MongoDB’s support for analytical nodes enabled Zepto to maintain consistent performance, ensuring effective real-time analytics across the platform.

The shift also streamlined Zepto’s ETL pipelines and archival processes, reducing management overhead and enabling faster deployment of new features.

“Post the migration, we observed a latency reduction of up to 40% for key APIs and handled throughput spikes, such as during campaigns, by enabling data compression and other optimisations. This has made our infrastructure more robust and scalable,” Singh said.

Scaling New Heights with AWS

Zepto’s success story is also powered by its strong partnership with AWS.

“We started Zepto about three years ago with just one dark store in Mumbai. Today, we’ve grown to over 200 dark stores and annualised sales north of INR 10,000 crore,” said Kaivalya Vohra, co-founder of Zepto. “From day one, we were clear that AWS was the way to go.”

AWS’ managed services and support allowed Zepto to launch new features rapidly while optimising costs. “AWS helped us achieve a quick MVP with credits from the AWS Activate program. As we scaled, the collaboration with AWS architects enabled us to come up with solutions no one had tried before,” noted Singh.

Zepto leverages AWS across the entire customer journey, from enhancing product discovery to streamlining last-mile logistics. Generative AI solutions on AWS have also enabled faster resolution times and improved customer satisfaction.

“AWS has been instrumental in helping us scale quickly while optimising costs. Its enterprise support and sponsorship for POCs have been invaluable,” Singh added.

The Pricing Dilemma 

Zepto is currently under fire for differential pricing algorithms on Android and iPhones. Several customers have expressed their frustration on social media platforms, speculating the possible reasons behind the stark difference in prices. 

Some believe the pricing is influenced by demographic and user device data, which could potentially favour Android users. The company has yet to officially comment on this issue.

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MongoDB, Inc. (NASDAQ:MDB – Get Free Report) Director Dwight A. Merriman sold 1,045 shares of the firm’s stock in a transaction on Monday, January 13th. The stock was sold at an average price of $242.67, for a total value of $253,590.15. Following the completion of the transaction, the director now owns 85,652 shares in the company, valued at $20,785,170.84. This represents a 1.21 % decrease in their ownership of the stock. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which can be accessed through this hyperlink.

MongoDB Trading Up 0.2 %

Shares of NASDAQ:MDB traded up $0.50 during trading on Wednesday, reaching $242.91. 1,057,983 shares of the stock were exchanged, compared to its average volume of 1,524,993. The firm has a market cap of $18.09 billion, a PE ratio of -88.65 and a beta of 1.25. The stock has a 50-day moving average price of $280.67 and a 200-day moving average price of $269.51. MongoDB, Inc. has a 12 month low of $212.74 and a 12 month high of $509.62.

MongoDB (NASDAQ:MDB – Get Free Report) last issued its quarterly earnings results on Monday, December 9th. The company reported $1.16 earnings per share (EPS) for the quarter, topping analysts’ consensus estimates of $0.68 by $0.48. The business had revenue of $529.40 million for the quarter, compared to the consensus estimate of $497.39 million. MongoDB had a negative return on equity of 12.22% and a negative net margin of 10.46%. The firm’s quarterly revenue was up 22.3% compared to the same quarter last year. During the same quarter in the prior year, the business posted $0.96 earnings per share. On average, sell-side analysts expect that MongoDB, Inc. will post -1.86 earnings per share for the current fiscal year.

Analyst Upgrades and Downgrades

Several research analysts have recently issued reports on the company. JMP Securities restated a “market outperform” rating and issued a $380.00 price target on shares of MongoDB in a research report on Wednesday, December 11th. DA Davidson raised their price target on MongoDB from $340.00 to $405.00 and gave the stock a “buy” rating in a research report on Tuesday, December 10th. KeyCorp raised their price target on MongoDB from $330.00 to $375.00 and gave the stock an “overweight” rating in a research report on Thursday, December 5th. Truist Financial reiterated a “buy” rating and set a $400.00 target price (up from $320.00) on shares of MongoDB in a report on Tuesday, December 10th. Finally, Loop Capital lifted their target price on MongoDB from $315.00 to $400.00 and gave the stock a “buy” rating in a report on Monday, December 2nd. Two equities research analysts have rated the stock with a sell rating, four have issued a hold rating, twenty-two have given a buy rating and one has assigned a strong buy rating to the stock. According to data from MarketBeat.com, the stock has a consensus rating of “Moderate Buy” and an average target price of $364.64.

View Our Latest Stock Report on MDB

Institutional Investors Weigh In On MongoDB

Several hedge funds have recently modified their holdings of MDB. Sanders Morris Harris LLC bought a new position in shares of MongoDB in the 4th quarter worth about $2,794,000. Covea Finance acquired a new stake in shares of MongoDB in the 4th quarter valued at about $3,841,000. Park Avenue Securities LLC grew its stake in shares of MongoDB by 24.3% in the 4th quarter. Park Avenue Securities LLC now owns 1,723 shares of the company’s stock valued at $401,000 after buying an additional 337 shares during the period. Assenagon Asset Management S.A. grew its stake in shares of MongoDB by 11,057.0% in the 4th quarter. Assenagon Asset Management S.A. now owns 296,889 shares of the company’s stock valued at $69,119,000 after buying an additional 294,228 shares during the period. Finally, Tealwood Asset Management Inc. acquired a new position in MongoDB during the 4th quarter valued at about $243,000. Institutional investors and hedge funds own 89.29% of the company’s stock.

About MongoDB

(Get Free Report)

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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Following this transaction, Merriman holds 85,652 shares indirectly through the Dwight A. Merriman Charitable Foundation, while directly owning 1,117,006 shares. An additional 520,896 shares are held indirectly by The Dwight A. Merriman 2012 Trust for the benefit of his children. The sale was executed under a pre-established Rule 10b5-1 trading plan. InvestingPro data shows MongoDB holds more cash than debt on its balance sheet, with 24 analysts maintaining positive earnings revisions. Get access to 8 more exclusive ProTips and comprehensive analysis through the MongoDB Pro Research Report.

In other recent news, MongoDB has seen a flurry of activity from analysts and investors alike. Guggenheim upgraded MongoDB shares from Neutral to Buy, setting a price target of $300. This upgrade is based on a discounted cash flow analysis and suggests a potential upside of 22%. Guggenheim predicts MongoDB’s total revenue growth for FY26 to mirror the conservative 15% growth rate set in the past two years, potentially performing better than FY24 rather than FY25.

In a significant financial move, MongoDB issued shares and redeemed convertible notes, allowing note holders to convert their debt holdings into equity in the company. MongoDB issued 5,662,979 shares of its common stock in this transaction. This strategic move aligns with MongoDB’s financial strategies and reflects its commitment to efficient capital structure management.

Several analysts have provided varied perspectives on MongoDB’s future performance. Tigress Financial Partners maintained a Buy rating, raising its price target to $430.00. Monness, Crespi, Hardt downgraded MongoDB’s shares to Sell, citing a slowdown in growth for MongoDB Atlas (NYSE:ATCO) and the recent resignation of the CFO. Macquarie initiated coverage on MongoDB with a Neutral rating and a price target of $300, acknowledging the company’s appeal among developers, particularly for AI applications.

In Q3 2025, MongoDB reported a 22% year-over-year increase in revenue, reaching $529.4 million. This growth was consistent across its subscription revenue, which also rose by 22% to $512.2 million, and its services revenue, which saw an 18% increase to $17.2 million. These recent developments provide a snapshot of MongoDB’s current financial health and market position.

This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.

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Harbor Capital Advisors Inc. decreased its position in MongoDB, Inc. (NASDAQ:MDB – Free Report) by 63.1% in the 4th quarter, according to its most recent filing with the Securities & Exchange Commission. The firm owned 1,301 shares of the company’s stock after selling 2,226 shares during the period. Harbor Capital Advisors Inc.’s holdings in MongoDB were worth $303,000 at the end of the most recent quarter.

A number of other large investors have also made changes to their positions in the company. Aigen Investment Management LP acquired a new position in shares of MongoDB in the third quarter valued at approximately $1,045,000. Geode Capital Management LLC boosted its stake in MongoDB by 2.9% in the 3rd quarter. Geode Capital Management LLC now owns 1,230,036 shares of the company’s stock worth $331,776,000 after purchasing an additional 34,814 shares during the period. B. Metzler seel. Sohn & Co. Holding AG bought a new position in MongoDB during the 3rd quarter worth about $4,366,000. Charles Schwab Investment Management Inc. raised its stake in shares of MongoDB by 2.8% in the 3rd quarter. Charles Schwab Investment Management Inc. now owns 278,419 shares of the company’s stock valued at $75,271,000 after purchasing an additional 7,575 shares during the period. Finally, Sanctuary Advisors LLC bought a new stake in shares of MongoDB in the second quarter valued at about $1,860,000. Institutional investors own 89.29% of the company’s stock.

Analyst Ratings Changes

MDB has been the subject of a number of research reports. Tigress Financial increased their price objective on MongoDB from $400.00 to $430.00 and gave the stock a “buy” rating in a report on Wednesday, December 18th. Truist Financial reiterated a “buy” rating and issued a $400.00 price objective (up from $320.00) on shares of MongoDB in a report on Tuesday, December 10th. Robert W. Baird increased their target price on shares of MongoDB from $380.00 to $390.00 and gave the stock an “outperform” rating in a report on Tuesday, December 10th. Royal Bank of Canada lifted their price target on shares of MongoDB from $350.00 to $400.00 and gave the company an “outperform” rating in a research note on Tuesday, December 10th. Finally, JMP Securities restated a “market outperform” rating and set a $380.00 price objective on shares of MongoDB in a research note on Wednesday, December 11th. Two analysts have rated the stock with a sell rating, four have assigned a hold rating, twenty-two have assigned a buy rating and one has given a strong buy rating to the company’s stock. Based on data from MarketBeat.com, the company currently has a consensus rating of “Moderate Buy” and an average target price of $364.64.

Check Out Our Latest Report on MDB

MongoDB Trading Up 0.9 %

MongoDB stock opened at $242.41 on Wednesday. The company has a market capitalization of $18.05 billion, a price-to-earnings ratio of -88.47 and a beta of 1.25. The stock’s 50 day moving average is $280.67 and its 200-day moving average is $269.51. MongoDB, Inc. has a 12 month low of $212.74 and a 12 month high of $509.62.

MongoDB (NASDAQ:MDB – Get Free Report) last issued its quarterly earnings data on Monday, December 9th. The company reported $1.16 EPS for the quarter, beating analysts’ consensus estimates of $0.68 by $0.48. MongoDB had a negative return on equity of 12.22% and a negative net margin of 10.46%. The firm had revenue of $529.40 million for the quarter, compared to analyst estimates of $497.39 million. During the same period in the prior year, the firm posted $0.96 EPS. The company’s revenue for the quarter was up 22.3% on a year-over-year basis. As a group, equities research analysts predict that MongoDB, Inc. will post -1.86 earnings per share for the current fiscal year.

Insider Buying and Selling

In other MongoDB news, Director Dwight A. Merriman sold 3,000 shares of the firm’s stock in a transaction on Thursday, January 2nd. The stock was sold at an average price of $237.73, for a total transaction of $713,190.00. Following the transaction, the director now owns 1,117,006 shares in the company, valued at $265,545,836.38. This trade represents a 0.27 % decrease in their position. The transaction was disclosed in a legal filing with the Securities & Exchange Commission, which is available at the SEC website. Also, CAO Thomas Bull sold 1,000 shares of MongoDB stock in a transaction on Monday, December 9th. The shares were sold at an average price of $355.92, for a total value of $355,920.00. Following the completion of the transaction, the chief accounting officer now directly owns 15,068 shares of the company’s stock, valued at $5,363,002.56. This represents a 6.22 % decrease in their ownership of the stock. The disclosure for this sale can be found here. Over the last three months, insiders have sold 23,776 shares of company stock valued at $6,577,625. 3.60% of the stock is owned by company insiders.

MongoDB Profile

(Free Report)

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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Transcript

Davis: I’m going to be talking about enabling developer productivity, an internal and intentional evolution of the platform. In case you were wondering or confused if my words were not clear enough in my description, this is not about Kubernetes, and it’s not about internal development platforms or internal developer platforms, but I want to talk about platforms. I’m Jennifer Davis. I’m an engineering manager at Google. I am also an author. I’m very passionate about building communities and enabling people in different ways.

Developer Productivity

The first part of this, I want to talk about developer productivity. What is it? It’s totally about lines of code, and the number of artifacts you make. It’s getting into that flow. It is? No, not at all. It’s hard to describe. Let’s think about it from a business outcome perspective. Ultimately, the business wants us to build more value, faster all the time. It’s not about an individual’s value. It’s about whatever your company is building, whether it’s a product or a service. If you’re building cars, it’s about building the whole car. If you focus on a single element of that car, the seats or the windows, you’re going to just create artificial bottlenecks that impact the whole team. You’ll be wasting your opportunities to improve. It’s not about the individual, it’s about the team and the whole.

If we look at the research coming out of the DevOps research folks from DORA, it’s been about nine years now that they’ve been doing this research, and there’s a new survey out right now that you can take and participate in. What they’ve done is identified a set of outcomes that are predicted by the team’s performance, the organization’s performance, and all of these are dictated by capabilities.

You can predict how performant a team is based on a number of things. When we think about it, it’s those components, those capabilities that define the developer experience. Those are things like, how hard is it to write code? How hard is it to maintain code? How quickly can you get feedback about your code that you’ve written? How much autonomy do you have in choosing things and selecting how you’re going to solve problems? Maybe you don’t get to say this is the problem, but you get to choose how you do those things. Those are the capabilities that can predict your performance. It’s about your developer experience.

There are hindrances to dev experience. A lot of times if you think about Conway’s Law and that organizations design the systems that will produce and deliver this, and it’s impacted by the communication structure, then those same challenges in anything that we use, we can see them. It’s one of my little hobbies, is to evaluate and look at what are the communication flaws I see and how different services are out there by what I can guess is going on within that company, based on their communication structures. In addition to just the dev experience, for me personally, or for you individually, it’s about thinking beyond ourselves. It’s something that some people have innate. It’s like, I see a problem.

I can imagine a world in which it’s better, it’s improved for more than one person, but for a whole set of folks. It’s ok if this is not something that’s innate for you, an individual’s experience does not define the DevEx of a product or a service. It’s more the set of experiences that people have. You might not care or need to care about DevEx. You might be the only one in a field. You might not have any competition. I promise you, if your service or product is valuable, someone else is going to look at your terrible experience and say, that’s an opportunity for me to do something better. You cannot care about DevEx, but ultimately you want to care about it at some point.

How do we combat this? It’s with this role called DevRel. DevRel is this interdisciplinary role that centers around people and relationships. Every company does DevRel a little different, but it has the same components of engineering and advocacy and product. It’s a way to combat releasing your org charts with your products and services. Everyone should embrace a little bit of DevRel. I spoke at QCon in London recently, and I was talking about DevRel, and I had totally made this assumption, everybody knows what DevRel is.

Some of the feedback I got, I realized I’m doing everyone a disturbance. I’m doing the exact thing that I talk about, which is making assumptions about what everybody knows. We’re all vulnerable to this, making assumptions, and assuming this is the way. Ultimately, DevRel is going to help you increase adoption, increase engagement, increase enablement, change perceptions about what your company does, but also change your perceptions about what your company does. It’s going to help you identify and drive change that better fits your product or services into the market.

I want to share some of my experience right now, what’s going on and what I do. I said I’m at Google. Really, you might think Google is this huge company. What do you have to worry about any of those? It’s not really a one, it’s more like there’s a lot of us all working at the same company. We’re enabled by different sets of tools and possibilities. My team within DevRel is an engineering team. We create samples. I get the meta of the meta in terms of DevEx. We build the platform that helps other contributors at our company and our partners to build samples. Those samples in themselves are a measure of the developer experience that our products and services have.

Once upon a time, we had a single product, App Engine, and so DevRel built samples for App Engine. Then, as Google Cloud grew, we had a split, a reorg to have focused capabilities per language, because we really care about the idiomatic language experience that every developer comes into an environment: what they’re looking for, what they’re trying to solve. If we show them a Java sample that actually follows some practices in Node, those are not going to sit well, people are going to have a bad experience. They’re going to feel friction. We reorged based on language. Then that was insufficient, we had so many products. Then we reorged based on product. A platform emerged of shared capabilities while building samples, but it’s all fractured, and things kept getting bolted on based on what people needed.

What that meant is, if a product was doing well, they would staff the DevRel team to build the samples, to build the documentation. You have an uneven set of samples in the catalog supporting customers, but customers aren’t coming around, going, I want A sample to do A thing. Sometimes that’s the case, but a lot of time it’s about a journey. I’m trying to build a website, what do I need? I’m trying to build a Pub/Sub like message delivery, how do I do this? When you have a team that’s on a volunteer basis, handling your platform management and contacting different stakeholders and managing their expectations, and then having a bunch of top-down driven initiatives as well, you’re not going to be able to accelerate as different parts of the org need different samples, you’re stuck. We were shipping our org chart.

We started thinking about, what is it that we’re actually trying to do? There’s like, step one, we want to increase value. What’s our value? It’s not just samples. It’s code that our users find valuable. Unless our users are able to be successful with these samples, their DevEx of using the platform, we’re not successful, we’re not doing something that’s meaningful. Ultimately, as humans, we want to build something that has meaning. We came up with a set of principles. What are the things that we want to minimize? What do we want to stop doing? What are we going to try to eliminate completely from the work that we’re doing that’s distracting us? We don’t want to build the wrong things. We want to minimize how much work we actually have in progress, so we can actually deliver samples to customers.

We want to stop context switching platform to staff, to our stakeholders, to actual individual samples, to friction logging. We don’t want to work on bugs. That feels weird. Why wouldn’t you fix bugs? How do you know that the samples that have bugs are actually the right set of samples? You’re cutting yourself short by focusing on something you don’t even know has value yet. Which comes to the final two really critical pieces, we weren’t learning from our mistakes. Everyone would run into a particular problem. They’d share that with the product teams, but it didn’t go across all of DevRel, and so everyone kept experiencing the same sets of challenges. Not following established practices. When it comes to samples, partly, samples are part of the individual products, but partly, samples are a product in themselves. That set of samples that you provide to people, that set of samples that support your documentation, if you have bad samples, you’re going to hinder people’s trust in your samples. You have to think about that as a whole, and you want to have a consistent voice in those samples.

The first step in thinking about your platform is identifying the value that you’re creating and those shared capabilities of the platform. What thing are you taking care of for other folks, so they don’t have to all be specialists in them? Where are we going? This is specific to my team. There is no single platform that works for everybody and everybody’s use case. It’s a journey that we all have to discover, which is part of why I’m so passionate about this subject. This is where we’re going. My hope is to enable and empower lots of contributors, including ourselves, and having a lightweight, flexible platform that enables the creation of much broader set of samples, hence the bigger purple cloud.

Platforms

I said platform, what is a platform? Kubernetes is a platform. Google Cloud is a platform. The platform is the combination of much more than just the tools and technology. It’s the tools, the technology. It’s the processes. It’s the workflows. It’s the collaboration, the communication. It’s learning and development. It’s the environment and culture that you create. Platform, of course, it includes the tools and technologies. We can think of this as, how are you solving your particular problem? If you start out trying to solve the technology challenges and just implement random tools, you’re not solving your underlying value.

You can’t just throw away what exists. If you go and architect something and just try to create the new thing, all of the things you have built in the past are not there, and people are going to get really frustrated and angry, and you’re not going to have adoption of your platform. You have to think about your constraints, what exists today. You also have to question your assumptions. I’m going to talk a little bit later about some of the assumptions we’ve made and how we’ve changed it.

Ultimately, platforms need to be lightweight and evolve. One of the constraints we have is we do all our sample development on GitHub. That might seem strange. Of course, that makes sense. You’re making it open and available to people. Internally, contributors want to use the tools they have available that they know. Why can’t we just use the Google tools? It comes with all these extra measurements. Why can’t we just do that? There are assumptions embedded in that, assumptions that we have as well. We had to question ourselves, are we using the right set of workflows? We determine, yes, we need to create these samples in the open, available for people to see, and be able to explore them and build trust.

We also need to build them here, in this external place, because that’s what our customers are doing. We are the zero of customer of understanding, how does this platform work? If we’re leveraging things internally to build stuff, we’re not seeing all the friction. We’re not experiencing the friction. We’re not getting that feedback back to the products. If it’s so bad, that is something that needs to be improved. It’s being aware of your constraints when it comes to your tools and technology, so that you know when and what to change and how to change it.

You also want to minimize human toil. It’s not making it so that I want to do the thing just because it’s hard. There’s a lot of things we can get machines to do. Some of the things that we use, for example, our GitHub Actions that allow us to label context of pull requests that come in, and basically set that information to who is the most apt and expert in that area to handle reviews on it. We also set up LinkedIn so that when something comes in, people get that fast feedback. Is there something that they need to correct before it actually makes it into the system, or before someone actually reviews it? We set and establish sets of guidelines. In addition to Google style guides for all the different languages we support, we set explicit tiered sets of responsibilities and expectations people have about our samples, and that’s to encourage people to follow and have that single voice.

Platforms include the processes and workflows. Wherever you start from, that’s where you start. You have to test what your assumptions are about those workflows. One of those I mentioned with using GitHub and working in the open. Within a team, you want to also establish some common work item vocabulary, basically set how you’re going to handle issues that come in, have a single intake, how you assess the cost of building things. That way people understand and can communicate, and you build that trust within the team. Trust is crucial for a high-performing team. If you have situations where people can question because work’s not out in the open, or there’s not transparency, or there’s not consistency, you can have distrust.

That person isn’t working on the important things that you say are important, they’re just doing their own thing. That didn’t take much time, where is the actual work and impact? By establishing a set of vocabulary about how we talk about work, it creates more confidence and understanding, as you can see over time. It’s not a, measure the performance of individuals, it’s sharing across a team how they’re performing, so people can build trust.

We also do something called friction logging, and it’s not just for products in development, but it’s also an activity that helps us to work and share information about stuff. Because in DevRel, one of the concerns is, is there like a half-life? Can you only be in DevRel for some amount of time? The truth is, I think everybody should be doing DevRel, but also being able to try things out and explore them as a zeroth customer. You get the opportunity to take on the empathy, look at the DevEx of your product or your service, explore a journey, and provide meaningful feedback to the people building that particular product or service.

It also helps when onboarding someone. We’d have a little exercise of doing a friction log as a team exercise to understand what is it that we’re making assumptions about that we shouldn’t actually assume. Maybe there’s missing knowledge that we haven’t documented. Maybe there’s practices that have evolved in the community and we’ve missed them, and this helps us instill and grow our culture. Which goes to the platform is the collaboration and communication. When you’re trying to solve something, it’s more than just you. It starts within the team. You definitely need open communication and an ability to provide feedback to each other. Because if everyone is just saying, yes, that’s great, you’re not getting that critical feedback to be better or to be able to understand different perspectives.

You need to establish that set of trust and ensure there’s not contempt happening in any way on the team, or stonewalling, not answering people’s questions. Key to this is not building an us and them across the org. Especially within DevRel, we have stakeholders across the whole organization. We can’t get into a mindset of, they just do this, and it causes us so much problems. Because the minute we get into that, we’re going to harm our ability to work with people. We have to come from a place of yes, and. There’s a component of thinking through, how do you do this, not just within your organization, but across the industry as well? The industry frames and changes things. It’s, people have choice.

People are going to take a selection of different possibilities and build things upon them. When you choose a service from here and choose a service from there, GitLab, Datadog, you don’t have the capability to say, I’m going to ignore everything else and not care. If you think about this interteam and across the industry, how we’re building our relationships and how we accomplish and solve problems, it’s really crucial to actually driving performance.

It’s about learning and development. One of the first things we did as we tackled our new team and started thinking as a holistic element of looking across the platform, not just for a specific set of products, we started thinking, we have to be able to scale. How are we going to scale? We just had a set of training where we trained everybody about, how do you update a sample? How do you submit a PR? How do you submit a change list for our documentation, so the change that you made actually shows up in the documentation? All of this is part of a normal cadence.

Instead of just saying, people can figure it out themselves, actually taking the opportunity and making time for people to uplevel. Making explicit documentation about what you chose to do and why, because ultimately, the decisions you make about anything, they have to be available for evaluation, or you’re going to keep evaluating the same options over and over as the platform changes, or the needs of the platform change. New technology and new tools come to be available.

One of the things we do with our samples that we create, as well as with the platform itself, is to document, why do we choose to do this thing? Why are we coding in the open? Why do we use GitHub? That’s a decision record. We want to take note of that. We encourage sharing, we call it show and tell. It doesn’t have any expectations. Sometimes people feel vulnerable about saying, it’s a demo, when it’s half-baked. It’s ok when it’s show and tell, you’re just showing and telling about something you learned, or something you accomplished, something you tested out.

I encourage people to contribute to open-source projects. That seems redundant, because we work in open source, but here’s the challenge, it becomes too insular and siloed. You don’t notice having to work with other people. When you go into open-source projects, you learn better how to evolve your platform, because you’re able to see the different practices across the industry and adjust your expectations of how things could or should work. It’s easy to get caught up in the today, and here’s the focus and here’s the energy.

When you’re contributing to an open-source project, it lets you step away and think about things in a slightly different way. Which goes to the platform is the environment and culture. What is it that you want out of your platform? What is the space that you want to create for people? Thinking about the team rituals and seeding them with things that you care about. Some of the ones I’ve seeded within my team is we start our meetings with music, it gives people a little time. Because we’re a distributed team, we want time for people to connect with each other, and maybe they’ve been busy doing something all week, that music just provides that little easing into that sharing, where we talk through, how are you doing? This is the team temperature check using zones of regulation.

It gives people, if they’re feeling safe, the space and time to talk about how they’re doing and feeling, showing that mutual care for each other. They don’t have to share if they don’t want to. We end the meeting with kudos, just a little bit of gratitude, sets everyone up for a happy rest of their day, maybe fuels them for the rest of the week. When people leave the team, we celebrate it. We don’t just say goodbye. We actually take time to celebrate on those things that we’ve built with them and done with them, and that builds up more trust into the actual building of the platform itself. We play. We create samples and demos that go beyond just, here’s this thing. We think about, how do we engage our active whimsy? That makes it so it’s approachable for other people. We built this train demo: it’s open source. The concept was this game of, can you build a set of components, a working architecture? The logic behind it we calculated, it was like this meta on meta situation where we’re using cloud to build a test on cloud and build education.

Intentionally Evolving the Platform

I’ve talked a little bit about the platform. I’ve talked a little bit about developer performance. Then, how do you evolve the platform? First is keeping in mind the people, because the people are core. A lot of the things I just talked about with parts of the platform are about people. You want to establish an active communication plan. You want to be telling people and informing people on a regular rhythm. You want to make sure you know who you’re talking to and why you’re talking to them. You want to create a RACI, and that’s basically setting up a plan of the clear roles and responsibilities so everyone knows. It’s like the contract. If you do these things, we’ll do those things. Once you’ve identified and documented them, you can embed them into your planning of your technology. Who has capabilities? What are those capabilities? What are the contracts that you’re making, and establish with samples.

For us, the person who owns or is accountable to their sample, if they don’t update their sample, and I can’t automatically update it, then it’s going to get marked as something that can be archived. We’ve agreed to that contract based on the RACI. It’s connecting the effort to the value so people understand, why am I working on this particular thing? Because it helps build value over here. It’s making sure to celebrate the wins.

You can identify the set of metrics that matter to you within your org, a starting place might be DORA or SPACE. When it comes to DORA, there’s a set of metrics that I mentioned earlier that have been shown to show software delivery performance. This is a starting place. For us, when I look at what our environment is, and these are updated metrics since the last time I gave a talk that included metrics, our samples, we have 13,798 samples that we need to monitor and update and maintain. There are another 6000 approximate samples that are not actually in our docs yet. We’re trying to reduce that count so that all of our samples are available in our documentation. We have 8352 distinct use cases, meaning there’s specific journeys that we’re explaining to our developers. How do we think about how we would measure performance or the experience?

Remember, our goal, ultimately, for our platform is a double set of requirements. Right now, we’re focusing on our contributor metrics. Ultimately, we want to empower developers who come to use Google Cloud. Right now, we’re trying to grow our catalog, so our problem is quantity and quality. Our metrics are evolved slightly from the DORA metrics. You can see the hints in them. We want to think about how costly is it to update a sample and to catch problems with it. What is the right amount of effort that we should spend on update our own samples? Areas that are easy to measure are things like time to ship. That’s from the point that you start to submit a PR to the point that it actually gets into documentation, that measurement. It’s shown that high-performing teams are able to do this in hours. It might not surprise you to hear that it takes days to weeks for some of our samples to ship as a baseline. That’s improved.

Rollbacks for us is when a sample goes out into the wild, and then we have to go and make changes to it. That means it’s not like, roll back your production, but something leaked through that actually caused problems, and did not help people. Then, how often we’re delivering samples. A hard one for us to measure is our system green. How much should we be spending on testing our samples? What is that quality? This is the first set of metrics we’ve established to define how productive our developers can be? How effective can they be? Based on these metrics, we can change and adjust what we’re doing.

The first thing we did was we friction logged the sample contribution experience. We’ve done this multiple times, and we’ve gained additional information each time. If you think about how large a company is, and you think about who possibly could help with something, with samples, we could have a large set of folks that could work on samples, except we’ve always thought about it from a, here’s the set of folks, the DPEs, the developer program engineers, they’re the ones working on this code. We want to make it self-service. We want anybody who is interested in contributing samples to be empowered to contribute samples. We need to take on that experience. Talk to the tech writers, talk to the advocates, talk to the sales engineers, talk to the support engineers, find out what is hard about doing this. We’ve uncovered a lot.

One of the challenges we identified is in our review capacity, thinking about how long it takes for code to get into production. Part of this, is there availability for someone to review the code? We realized over time we’d had this set of patterns. We had a whole mentoring program. It took months to get to reviews. We just did not have that ability anymore to have that long lead time. We are taking a risk. We want to trust people to do the right thing, but we want to hold them accountable and make sure we’re measuring and seeing the impact of people’s reviews. Then, we want to recognize the quality behaviors. We have little badges to showcase when people are quality reviewers.

We decided to eliminate flaky testing. Originally, we did some research, and we were like, 78% of our alerts are noise, but they are solving some issues, so maybe we’ll progressively fix this problem. We determined that actually we’re not going to get there anytime soon, and we should quell the noise, so we’ve eliminated our flaky testing. We’re trying out AI. I want to say that for us, core to samples is trust. We know that people copy and paste our sample code directly into their production environment. I’m not saying that’s what they should do, but we recognize it’s what they do. There are things that we have found that we’re exploring with small experiments to determine areas where we can improve the overall experience.

When people file issues across our 100 and something odd repos, what if we’re able to assess things more quickly and consistently based on training from our previous issues to get better results in responding to specific types of issues. We’ve also looked at metadata generation, so that 19,000 samples, 7000 approximately, that are not embedded in documentation. Part of that is because there’s no metadata associated, meaning their title and description, like the intent of the sample. Because the model is trained specifically on our samples, it can provide context and help us to initiate a set of descriptions that helps us get our samples in the autogenerated pages.

We’ve also found that it’s helpful in terms of giving feedback on PRs, so we have those set of extensive style guides. It takes a reviewer knowing and understanding, it takes a contributor knowing and understanding all of those components. If we train a model directly on our style guides, we’re able to get a specific set of feedback that’s helpful that says, here’s where you’re having this problem. It links to the specific style guide issue, and that provides a better experience.

Recap

I’ve talked a lot about different pieces of this, in terms of what is developer productivity and platforms, and my thoughts on them, and about intentionally evolving your platform to solve the value that you are trying to build for your company or your service or your platform. It’s really important, ultimately, when we think about what is the dev experience, and investing some amount of time in that dev experience to help each one of us solve problems that are better for us as an industry.

Questions and Answers

Participant 1: Imagine that I am an IC, an individual contributor in my company, and my company has small silos, each sub-project has their own APIs, their own SDK. When my customers use those sub-projects, each SDK would look different. Being an IC in one of those projects, how can I influence my peers to start to discuss about developer productivity of how to have a cohesive experience over all the platform?

Davis: It goes to the whole culture of the environment. When you’re in a space where your company, it’s very siloed, and that’s what happens, you have to have some kind of leadership change that supports and encourages it. Coming from the grounds up, if you are in this situation, you can reach out and create a technical leads program. That’s one of the things that someone started at Google, actually. It encourages and starts discussions across. When people find these common problems, people want to help. Another part of it is navigating how you’re discussing and sharing or advocating for the problem. When we talk to leaders, as an IC and you’re going to your technical lead, or you’re not considered an official technical lead, but you see a problem.

If you frame it as, there’s this problem, and I need to fix it. In this case, we’re shipping all these APIs, and they’re all different, and the user experience is not quality. It seems obvious, there’s a problem, we should fix this. Ultimately, it comes down to communicating in the language of whoever you’re talking to and knowing what’s important to them. In your case, it’s like really challenging, because you can inspire and get everyone on board, yes, but then do you have investment to make change. You speak to, depending on how people are motivated, all our competitors are doing this, look at that. That’s one way.

Another way is, “I did a friction log. Here’s the things that create a lot of friction”. Talk to support engineers. Get that support there. If you can reduce support costs, because those are very expensive, like by the time something is problematic in the environment and a customer’s reporting, that’s costly. Or if you can improve people’s productivity, that’s a set of things that can change leaders’ minds. You don’t talk about it from the problem. You talk about it from the outcome and how it will support things.

Participant 2: You have 15 awesome examples of things to work on, if you were to pick one to start with, which one would it be?

Davis: My first step for me was figuring out what the problem was. I’ve described a lot of problems, but I didn’t describe the big one. The big one is fragmentation, so that we’re spending a lot of effort spending. The very first thing is to figure out, is there areas you’re spending? Then navigate how you talk to people, your leadership, your peers, your reports, whatever the case is, and identify how you can help people change their minds. It’s not easy. Getting people to think about disabling flaky bot was hard. It takes time to get to a decision where people are comfortable because you’re making change. You don’t want to do wholesale big changes, so you have to identify, what is going on? What are the risks? What are people afraid of? What are people wanting? What are people valuing? Once you establish that, you can tackle whatever the next thing is, and be willing to fail.

Participant 3: I have a question related to one of the measurements that I look at when I try to measure the engagement and motivation of my developers and data scientists. I would like just to get your opinion on that. They are telling us that they would like to see the connection between their actual work and the mission and vision of the company. Sometimes for us as managers, leaders, it’s easy to see that kind of connection, but it’s hard actually to break it down in actual projects, and most importantly, to show them the linkage between their everyday work and the vision, mission of the company or the organization. What would be your advice for this kind of work as a manager and leader?

Davis: If you think about it, and I’m going to add a little more context, samples, one of the things we want is we want to trust. In open source, you really want people to trust you. Any time you talk about tracking and data collection, because you want to collect data to improve, not to do anything bad, but to improve, it causes problems. Then, how do you, as an IC at a company, identify what changes actually matter and what’s valuable? As a whole, our samples, people can go to GitHub, and they can go copy and paste, but how do I know it’s actually helpful?

One thing is, depending on the set of abilities of tracking you have within your teams, you can identify and see how many things are deployed. We have something called Jumpstart solutions, where we can see direct impact of if someone deploys a solution, how long it stays deployed, how it evolves. Are they sticky? Are we enabling people? Are they learning more? What does that impact? When people can see those real numbers of you’ve enabled or you’ve engaged, it’s great, but it’s tricky. You have to map things into a different framing.

Part of this is getting people to talk about what you’re working on, and then tying it explicitly into the larger orgs, and repeating over again the message, “This is to do this, and it’s driving these sets of changes”. Recognizing that if they’re not seeing that value return, if the feedback loop isn’t bringing back and changing their work. If you’re not doing retros or post-mortems or whatever you want to call it, and you’re not incorporating change, it just feels like they’re throwing stuff out into the void. It’s really important to incorporate practices that also enable the learning loop.

Participant 4: You are talking about developer productivity. We have several smart developers on the team who want to be productive, more productive than they are right now, but they all have different definitions of what productive means. What’s your recommendation on reconciling the definitions and how to do it in politically nice terms without offending them much?

Davis: When we think about productivity, that’s why part of it is productivity of a team as a whole versus productivity as individuals. Individuals can be productive in whatever way they want, how they measure, it’s great. For me, I will tell my boss, I need my cookies, because when I get my cookies, they’re not real cookies, it’s just like, good job, that’s my cookie. It’s not even qualitative, it’s just occasionally I need that. I have my own set of metrics for my performance, but it’s one of the things why it’s really crucial, what you measure is going to influence what you get. If you say I need lines of code, you’re going to get more lines of code.

If you say, I want clicks to a URL, I know how to write a nice little tool that will automate clicks to a URL, because I value about different things. To change what you’re saying a little bit, it’s ok for everyone to have different measures of productivity, but clearly articulating with a common set of work vocabulary, clearly articulating what the goal is. We’re building cars, your part is that cog. If you have too many cogs, this other piece needs focus, and this is creating a bottleneck. Encouraging people to have mutual care and reciprocal trust to engage and enable each other. It’s really important as a manager to note when someone is not performing and to manage that in a kind way, because ignoring performance issues harms the team.

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Covea Finance bought a new position in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) during the fourth quarter, according to its most recent Form 13F filing with the Securities & Exchange Commission. The firm bought 16,500 shares of the company’s stock, valued at approximately $3,841,000.

Several other institutional investors and hedge funds have also recently added to or reduced their stakes in the company. Hilltop National Bank grew its holdings in shares of MongoDB by 47.2% during the 4th quarter. Hilltop National Bank now owns 131 shares of the company’s stock worth $30,000 after purchasing an additional 42 shares in the last quarter. Quarry LP boosted its stake in MongoDB by 2,580.0% during the second quarter. Quarry LP now owns 134 shares of the company’s stock worth $33,000 after buying an additional 129 shares in the last quarter. Brooklyn Investment Group bought a new stake in MongoDB in the 3rd quarter valued at $36,000. GAMMA Investing LLC raised its stake in shares of MongoDB by 178.8% in the 3rd quarter. GAMMA Investing LLC now owns 145 shares of the company’s stock valued at $39,000 after buying an additional 93 shares in the last quarter. Finally, Continuum Advisory LLC boosted its position in shares of MongoDB by 621.1% during the 3rd quarter. Continuum Advisory LLC now owns 137 shares of the company’s stock valued at $40,000 after acquiring an additional 118 shares in the last quarter. 89.29% of the stock is currently owned by institutional investors.

Insider Buying and Selling at MongoDB

In other MongoDB news, CAO Thomas Bull sold 1,000 shares of the stock in a transaction on Monday, December 9th. The shares were sold at an average price of $355.92, for a total value of $355,920.00. Following the sale, the chief accounting officer now directly owns 15,068 shares in the company, valued at approximately $5,363,002.56. This trade represents a 6.22 % decrease in their ownership of the stock. The transaction was disclosed in a document filed with the SEC, which is accessible through the SEC website. Also, CEO Dev Ittycheria sold 2,581 shares of the business’s stock in a transaction on Thursday, January 2nd. The shares were sold at an average price of $234.09, for a total transaction of $604,186.29. Following the completion of the transaction, the chief executive officer now directly owns 217,294 shares of the company’s stock, valued at $50,866,352.46. This trade represents a 1.17 % decrease in their position. The disclosure for this sale can be found here. Over the last quarter, insiders have sold 23,776 shares of company stock valued at $6,577,625. 3.60% of the stock is currently owned by company insiders.

MongoDB Trading Up 0.9 %

Shares of NASDAQ MDB opened at $242.41 on Wednesday. The firm has a market capitalization of $18.05 billion, a PE ratio of -88.47 and a beta of 1.25. The firm’s 50-day moving average is $280.67 and its 200-day moving average is $269.51. MongoDB, Inc. has a 1 year low of $212.74 and a 1 year high of $509.62.

MongoDB (NASDAQ:MDB – Get Free Report) last announced its quarterly earnings data on Monday, December 9th. The company reported $1.16 earnings per share (EPS) for the quarter, beating analysts’ consensus estimates of $0.68 by $0.48. MongoDB had a negative net margin of 10.46% and a negative return on equity of 12.22%. The firm had revenue of $529.40 million for the quarter, compared to analysts’ expectations of $497.39 million. During the same period last year, the firm earned $0.96 earnings per share. The business’s revenue for the quarter was up 22.3% on a year-over-year basis. As a group, equities research analysts anticipate that MongoDB, Inc. will post -1.86 earnings per share for the current fiscal year.

Analyst Upgrades and Downgrades

Several research analysts recently issued reports on MDB shares. Mizuho raised their price target on shares of MongoDB from $275.00 to $320.00 and gave the stock a “neutral” rating in a research note on Tuesday, December 10th. Tigress Financial boosted their price target on MongoDB from $400.00 to $430.00 and gave the company a “buy” rating in a research note on Wednesday, December 18th. Macquarie began coverage on MongoDB in a research note on Thursday, December 12th. They set a “neutral” rating and a $300.00 price objective for the company. KeyCorp boosted their target price on shares of MongoDB from $330.00 to $375.00 and gave the company an “overweight” rating in a research note on Thursday, December 5th. Finally, Wedbush upgraded shares of MongoDB to a “strong-buy” rating in a research report on Thursday, October 17th. Two research analysts have rated the stock with a sell rating, four have assigned a hold rating, twenty-two have issued a buy rating and one has issued a strong buy rating to the company. Based on data from MarketBeat.com, the company presently has a consensus rating of “Moderate Buy” and an average target price of $364.64.

Get Our Latest Stock Analysis on MDB

MongoDB Company Profile

(Free Report)

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

Posted on mongodb google news. Visit mongodb google news

Harbor Capital Advisors Inc. lessened its holdings in shares of MongoDB, Inc. (NASDAQ:MDB – Free Report) by 63.1% during the 4th quarter, according to its most recent filing with the Securities and Exchange Commission. The firm owned 1,301 shares of the company’s stock after selling 2,226 shares during the quarter. Harbor Capital Advisors Inc.’s holdings in MongoDB were worth $303,000 as of its most recent SEC filing.

Other hedge funds and other institutional investors have also recently added to or reduced their stakes in the company. Hilltop National Bank increased its position in shares of MongoDB by 47.2% during the fourth quarter. Hilltop National Bank now owns 131 shares of the company’s stock worth $30,000 after acquiring an additional 42 shares in the last quarter. Quarry LP boosted its stake in MongoDB by 2,580.0% in the 2nd quarter. Quarry LP now owns 134 shares of the company’s stock worth $33,000 after purchasing an additional 129 shares during the period. Brooklyn Investment Group bought a new position in MongoDB during the 3rd quarter worth about $36,000. Continuum Advisory LLC raised its stake in shares of MongoDB by 621.1% in the 3rd quarter. Continuum Advisory LLC now owns 137 shares of the company’s stock valued at $40,000 after purchasing an additional 118 shares during the period. Finally, GAMMA Investing LLC lifted its holdings in shares of MongoDB by 178.8% in the third quarter. GAMMA Investing LLC now owns 145 shares of the company’s stock valued at $39,000 after purchasing an additional 93 shares in the last quarter. 89.29% of the stock is currently owned by institutional investors.

MongoDB Price Performance

MDB traded up $7.40 on Wednesday, hitting $249.81. 121,113 shares of the stock were exchanged, compared to its average volume of 1,432,734. MongoDB, Inc. has a 12 month low of $212.74 and a 12 month high of $509.62. The firm has a market capitalization of $18.60 billion, a price-to-earnings ratio of -91.17 and a beta of 1.25. The business has a 50-day moving average of $280.67 and a two-hundred day moving average of $269.51.

MongoDB (NASDAQ:MDB – Get Free Report) last posted its earnings results on Monday, December 9th. The company reported $1.16 earnings per share for the quarter, topping analysts’ consensus estimates of $0.68 by $0.48. The firm had revenue of $529.40 million for the quarter, compared to analyst estimates of $497.39 million. MongoDB had a negative net margin of 10.46% and a negative return on equity of 12.22%. The company’s revenue for the quarter was up 22.3% compared to the same quarter last year. During the same period in the previous year, the firm posted $0.96 EPS. Equities research analysts expect that MongoDB, Inc. will post -1.86 earnings per share for the current fiscal year.

Analysts Set New Price Targets

A number of research analysts recently issued reports on MDB shares. Rosenblatt Securities started coverage on MongoDB in a report on Tuesday, December 17th. They set a “buy” rating and a $350.00 price objective for the company. Stifel Nicolaus raised their price target on shares of MongoDB from $325.00 to $360.00 and gave the stock a “buy” rating in a research note on Monday, December 9th. Tigress Financial boosted their price objective on shares of MongoDB from $400.00 to $430.00 and gave the stock a “buy” rating in a research report on Wednesday, December 18th. Monness Crespi & Hardt cut shares of MongoDB from a “neutral” rating to a “sell” rating and set a $220.00 target price for the company. in a report on Monday, December 16th. Finally, Mizuho lifted their price target on shares of MongoDB from $275.00 to $320.00 and gave the company a “neutral” rating in a research note on Tuesday, December 10th. Two equities research analysts have rated the stock with a sell rating, four have given a hold rating, twenty-two have given a buy rating and one has given a strong buy rating to the company. According to data from MarketBeat.com, the company presently has an average rating of “Moderate Buy” and a consensus target price of $364.64.

View Our Latest Report on MongoDB

Insider Transactions at MongoDB

In other MongoDB news, CFO Michael Lawrence Gordon sold 5,000 shares of the stock in a transaction that occurred on Monday, December 16th. The stock was sold at an average price of $267.85, for a total transaction of $1,339,250.00. Following the transaction, the chief financial officer now directly owns 80,307 shares in the company, valued at approximately $21,510,229.95. This represents a 5.86 % decrease in their position. The transaction was disclosed in a filing with the Securities & Exchange Commission, which is accessible through this link. Also, CAO Thomas Bull sold 169 shares of MongoDB stock in a transaction on Thursday, January 2nd. The shares were sold at an average price of $234.09, for a total transaction of $39,561.21. Following the completion of the sale, the chief accounting officer now owns 14,899 shares of the company’s stock, valued at $3,487,706.91. This represents a 1.12 % decrease in their position. The disclosure for this sale can be found here. Insiders sold a total of 23,776 shares of company stock worth $6,577,625 over the last three months. 3.60% of the stock is owned by company insiders.

MongoDB Company Profile

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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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