MongoDB (MDB) Q4 FY2023 Earnings Review

With MongoDB’s Q4 earnings report following most peers in the software infrastructure space, investors were bracing for decelerating revenue growth and a conservative guide for the upcoming year. MongoDB delivered just that. While Q4 notched a nice beat on revenue with growth of 36% annually, the preliminary guide for FY2024 came in at just 16% growth, almost 10% below analyst estimates.

That level of deceleration would normally torpedo a stock, but MDB closed the following day lower by about 8%. In subsequent weeks, the stock recovered that drop and recently closed above its pre-earnings price. Granted, most software stocks benefited from a favorable boost over the last week. This price action implies that the market is anticipating a recovery for the software sector and that preliminary revenue guidance may be conservative.

While sales growth is struggling, MongoDB is demonstrating a rapid improvement in profitability. Q4 was their highest level of Non-GAAP operating margin to date, passing 10% for the first time. This coincided with a 400 bps improvement in gross margin and record free cash flow. Looking forward, preliminary estimates for EPS surpassed analyst targets. The full year FY2024 operating margin target is starting at 5%, slightly higher than what was delivered in all of FY2023. I expect this to increase as the year progresses, just as it did in 2022.

Similar to peers, MongoDB’s explanation for subdued revenue growth is slower spend expansion by existing customers. In times of economic stress, MongoDB is hit by a double whammy. As a consumption business, if their customers experience a slowdown in digital activity, then Atlas usage decreases. Additionally, customers will delay workload migration projects, as they try to manage costs. These factors combined to force MongoDB leadership to set a low revenue growth target for FY2024, expecting that these headwinds will continue.

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At the same time, the consumption model can cut both ways. If the economic tide turns, those compounding headwinds could become tailwinds. Added to this potential reversal with existing customer activity would be the contribution from new customers. Through this period of macro pressure over the last year, new customer activity has remained largely intact. MongoDB grew total and Direct Sales customers at about the same rate as in prior quarters. Additionally, the increase in large customers (spending $100k+) matched the record additions in Q4 a year ago.

This leaves investors in a quandary, similar to consideration for the rest of the software infrastructure space. Leadership at these companies had to provide a preliminary view for the full 2023 calendar year during a tricky time. Most chose to set revenue growth targets much lower than in prior years. While they will probably not return to the hypergrowth of 2020-2021, they very well may beat the conservative guides set for 2023.

And this is likely what the market is anticipating. As interest rate increases slow down and eventually stop, the ensuing stability may allow enterprises to feel comfortable loosening the constraints on software projects and cloud migration. A return to growth with existing customer spend, combined with the same ramping of a backlog of new customers, should drive a bottoming and subsequent reacceleration of revenue growth for software service providers.

This revenue reacceleration will coincide with the ongoing cost reduction and operating efficiencies at these companies now. The outcome should be an ideal mixture of revenue growth with favorable free cash flow. If the economic backdrop cooperates, I think investors will have this set-up to anticipate in 2024. Of course, if the macro situation worsens, we will get more of the same.

Regarding MongoDB, a surface level interpretation of MongoDB’s revenue performance would be that its growth has peaked, competition is taking sales and their multi-model data storage strategy is no longer relevant. Yet, none of these risks are materializing. MongoDB is still attracting new customers, with established ones finding more ways to consolidate point database workloads onto MongoDB’s platform. Their addressable market is huge, estimated at $84B last year and growing to $138B by 2026.

And then there is AI. Putting aside the hype, the flurry of activity around AI should generate tangible benefits for MongoDB. These center around an influx of new AI-powered companies building digital experiences, a heightened focus by enterprises on unlocking their data and the increase in developer productivity allowing enterprises to work through their digital transformation backlog even faster. Higher productivity also means lower staffing costs, freeing up more budget for software infrastructure.

To decide on the path forward for MDB stock, let’s first step back and examine MongoDB’s market, how their product fits it and whether the competitive landscape has changed. Then, we can review the Q4 results and forward estimates to see if stunted growth is a result of broader macro conditions, or some issue with MongoDB’s product fit. I think it is the former and am anticipating growth to pick up as the year progresses.

MongoDB Product Strategy

While macro is pressuring usage of customer applications and slowing down enterprise expansions, MongoDB’s product strategy remains the same and still resonates with developers. Their product vision is to deliver a reliable, scalable and easy to use platform to serve as the transactional data store for modern software applications. This hinges on their flexible document-oriented data model, which aligns with how developers work with data within applications.

This approach represents an evolution of the traditional relational data model. While compact, a relational model rarely maps directly to how data is stored in an object-oriented application, relying on an ORM to serve as a translation layer between the two. The document model eliminates this friction by mirroring the structure of data within applications, making it easier for developers to use in most cases. JSON is becoming ubiquitous as an open file format for data storage within applications and for data transfer between them.

As a file, JSON naturally aligns with the document storage model. With productivity and usability as key considerations, developers want to focus on the more interesting and impactful aspects of their applications. Mapping fields in a JSON representation to columns in a relational database is a waste of time. In the past, when relational databases greatly outperformed other storage models, this optimization was necessary. With better hardware and software improvements, this performance advantage no longer justifies the extra effort. AI training data and LLM’s naturally gravitate towards a document model for storage and graph queries for look-ups, further diminishing the relevance of relational models.

Even with these fundamental advantages of the document model, MongoDB’s strategy has been to address adjacent data storage use cases as well. They recognized that the document model can support the query and storage patterns of most other data models. To abstract the differences, the MongoDB team built a Unified Query API to facilitate the translation of different data models into the core document store. These data types can be easily modeled in a document form and then queried through the API using the same access patterns typical for that data type. These extensions address most “document adjacent” data models like key-value, time series, graph, geospatial, search and even basic relational.

Another motion of MongoDB’s platform expansion has been to support application specific use cases. The first of these was to provide a mobile app data sync, which enables mobile devices to maintain a lightweight copy of data for a user in close proximity to the device. This replaces other cloud-based mobile app data stores like Google’s Firebase.

The next use case expansion was search, which is functionally based on an index of documents, providing a natural extension to MongoDB’s core data engine as a document store. The MongoDB team leveraged the same search libraries based on Apache Lucene that are used by other dedicated search solutions. This allowed MongoDB to be used for text search and more recently faceted searches, providing a replacement for Elasticsearch and SOLR.

The benefit to using MongoDB for search is the proximity of the transactional data to the search index. A normal configuration with Elasticsearch or SOLR requires a data sync job to transmit updates from the transactional database to the search index. This process can be brittle, introduces a delay and encumbers DevOps with another system to manage. MongoDB’s search architecture eliminates these disadvantages.

More recently, the MongoDB team has been continuing this trajectory into new use cases by adding support for analytical workloads through an interface to their time series data type. This allows applications that collect, process and distribute large amounts of time series data (primarily IoT) to leverage MongoDB as their back end.

Through these additional data types and workloads, the sales team can make the argument to potential customers that MongoDB can be leveraged for many types of applications. This allows the customer to eliminate data storage point solutions that address just one of these workloads. The benefit to the customer is fewer vendor relationships to manage, a simpler data interface for developers and less cost through volume discounts.

MongoDB’s CEO summed up the approach by providing an anecdote from a customer meeting at AWS re:Invent.

“So what we’ve done is a first-class transactional platform, and now we’re expanding the platform to do things like search and analytics,” he noted. “I was just meeting with a customer who was thinking about Mongo for their transactional platform, elastic for the search platform, and a graph database for a special use case. And, and we said, ‘You can do all that on MongoDB.’”

MONGODB CEO, INTERVIEW WITH THECUBE, DECEMBER 2022

Go-to-Market Strategy

Beyond this product strategy, MongoDB has been pursuing newer go-to-market approaches. These involve two initiatives – stronger collaboration with the hyperscalers and expanded partnerships with system integrators. For the hyperscalers, MongoDB has been rolling out deeper integrations and co-selling relationships. Over the last two years, they have announced strategic partnerships with GCP, AWS and Microsoft Azure. These relationships have strengthened in spite of each hyperscaler offering competing products in the past, like DocumentDB from AWS and Cosmos DB from Microsoft.

In March 2022, MongoDB announced an expanded collaboration with AWS. The agreement with AWS built on the existing multi-year relationship between the two companies, aimed at driving customer adoption of MongoDB Atlas on AWS. In an effort to further improve the customer experience, both companies agreed to collaborate across sales, customer support, solution architecture, marketing and other areas to make MongoDB Atlas a better experience for developers on AWS globally. This includes increased workload migration incentives and enhanced tools to help customers move from legacy technologies in on-premise data centers to MongoDB Atlas on AWS.

The partnership will support MongoDB’s expansion into more AWS Regions across the globe and the US Public Sector with FedRAMP authorization. In February 2023, MongoDB announced that it achieved the FedRAMP Moderate Authorized designation for MongoDB Atlas for Government. As a result, thousands of  government organizations leveraging AWS will be able to use Atlas for Government to build and deploy secure, highly-scalable, distributed applications in the cloud.

Google Cloud Platform (GCP) struck a similar agreement with MongoDB in April 2022. In this case, it is a pay-as-you-go offering available directly in the GCP console. Customers will just be billed for MongoDB Atlas based on their consumption, with no up-front commitments. This makes provisioning seamless, as customers can initiate the relationship through GCP and consolidate costs onto their existing GCP bill. Atlas is deeply integrated with a number of other GCP services including BigQuery, Tensorflow, Cloud Run, App Engine, EventArc, Cloud Functions, Google Kubernetes Engine (GKE) and Dataflow. Additionally, Google does not offer a substitute product for MongoDB, making their alignment even more natural.

While Microsoft Azure has the most directly competitive offering in Cosmos DB, they too are actively collaborating with MongoDB. In October 2022, they announced an expanded relationship. MongoDB Atlas is available on the Microsoft Azure Marketplace. With the agreement, Microsoft customers can apply Azure committed spend to Atlas usage. This can be done on a “Pay-as-you-go” model without requiring upfront commitments.

Additionally, Microsoft made MongoDB one of only two database partners for their new Microsoft Intelligent Data Platform Partner Ecosystem. The Microsoft Intelligent Data Platform deeply integrates operational databases, analytics, BI and data governance products into a unified platform. This platform, which is also integrated with the Microsoft Cloud, enables a seamless experience and intuitive collaboration between all participants in an enterprise data organization. Further underscoring the possibilities stemming from this relationship, the MongoDB team published a blog post in February extolling the benefits of using MongoDB Atlas as a smart manufacturing data hub on Microsoft Azure.

These tighter relationships with the hyperscalers were highlighted in the Q4 earnings release.

The Company signed a new 5-year strategic partnership agreement with Microsoft Azure, including commitments to technical integrations, acceleration of joint go-to-market activities, as well as joint focus and incentives to migrate MongoDB on-premises deployments to Atlas on Azure. Recently, MongoDB expanded its multi-year partnership with Google Cloud to include a number of new, joint go-to-market programs, along with an initiative to accelerate startups’ data journeys. Additionally, AWS awarded MongoDB Marketplace Partner of the Year for the Europe, Middle East, and Africa (EMEA) region after witnessing strong growth among joint customers in that geography during the year.

MongoDB Q4 FY2023 Earnings Report

At the end of the day, the hyperscalers still make money from customers that utilize MongoDB Atlas on their cloud. The primary source is the additional compute and storage that MongoDB is using to process and store their customers’ data. In addition, MongoDB can bring their on-premise customers with EA licenses to the hyperscaler partner when those customers are ready for a cloud migration. The hyperscalers are realizing that pushing their internal solution on a customer who has already decided to leverage MongoDB could result in them losing the deal to another hyperscaler.

Competitive Landscape

I have provided in-depth analysis of the competitive landscape for transactional databases and MongoDB’s position in prior blog posts. MongoDB is the most popular document-oriented database solution on the market. Additionally, with their expansion to other document-adjacent data types (time series, key-value, graph, wide column), MongoDB intends to deliver a broader multi-model data platform. Plus, the solution provides support for unique workloads like mobile, in-app analytics, charting and search.

As the data platform’s applicability expands, it becomes suitable as the backing data store for many applications within the same enterprise. Most modern enterprises are allowing developers the freedom to choose their technology stack from a preset selection of options. MongoDB’s go-to-market with large enterprises involves getting anointed as one of these sanctioned solutions. Then, the broad popularity, ease of use and familiarity of MongoDB with developers can drive their selection for new application workloads and legacy database refreshes.

As developers were empowered by enterprise engineering teams to make tool selection, the result has been a sprawl of point solutions to address multiple data types and workloads. The MongoDB value proposition is to provide a single platform to replace most database types. A reasonable argument can be made that MongoDB is a suitable drop-in for key-value, search, time series, graph, wide column and reverse index data types, as well as a denormalized relational schema.

The benefits of a single data platform stem from cost savings, fewer vendor agreements, higher developer productivity and reduced DevOps overhead. Additionally, MongoDB clusters can be located on and share data across all three hyperscalers (GCP, AWS and Azure). This cross-cloud capability is appealing as enterprise development teams seek to avoid lock-in with one hyperscaler.

MongoDB’s strategy with enterprises is to land with a single application and then expand into many. This has been successful with a number of large enterprises, with several examples highlighted on the Q4 earnings call. And while we would assume that the majority of MongoDB’s customers would be the digital natives, the opposite is true. MongoDB’s largest customers are mainstream enterprises in finance, manufacturing, healthcare, retail and technology. They even have a number of government agencies as customers.

To assess MongoDB’s position in the market, we can refer to third party industry analysts. A reasonably objective indicator of data storage engine usage across all categories is provided by DB-Engines. They maintain a ranking of popularity of solutions on their web site, with an overall score and an indication of change in magnitude compared to the prior month and the prior year. This is constructed from a combination of inputs pulled from various public forums, discussion boards, web sites and job postings, which are all heavily developer influenced.

If we look at rankings for document databases and their multi-model adjacents, MongoDB is well ahead of any competitive offerings. The second place position goes to DynamoDB and that has a score less than 1/5 of MongoDB’s ranking. Further, no other offering is making significant progress up the rankings, with all solutions maintaining about the same relative level of popularity over time.

Other third-party industry analysts rank MongoDB as a leading solution for database workloads. In December 2022, Gartner named MongoDB as a leader in their Magic Quadrant for Cloud Database Management Systems. This category was very broad and MongoDB wasn’t even in the rankings in 2021. To land in the Leaders quadrant in their inaugural appearance is a major acknowledgement. Other leaders were major technology providers who span multiple database categories, like AWS, Azure, Google and Oracle. MongoDB was the only independent, non-relational focused solution named as a leader.

Similarly, in November 2022, MongoDB was placed in the Leaders circle by Forrester in their Wave report on Translytical Data Platforms. Translytical data platforms are optimized for transactional workloads like a traditional OLTP database, but add support for real-time analytics, which is increasingly becoming a requirement for data-rich applications.

Against this backdrop, MongoDB was evaluated within a pool of 15 providers. Forrester placed them in the Leaders circle, with only four other vendors. They ranked highest among providers that exclusively focus on database solutions with a single product. MongoDB was awarded the greatest score on 11 out of 26 of the objective criteria.

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Q4 Earnings Results

Now that we have reviewed MongoDB’s market opportunity, product strategy and the competitive landscape, let’s look at how these relate to the most recent earnings results. The critical question for investors will revolve around the durability of MongoDB’s revenue growth and whether we will see increases to their preliminary FY2024 guide as the year progresses. Additionally, the rapid improvement in profitability provides new support for the stock as the market shifts away from exclusive focus on growth metrics.

Revenue

Revenue growth had been decelerating over the course of FY2023 (calendar 2022). MongoDB started FY2023 with 57% annual growth in Q1. This decreased to 53% in Q2 and further to 47% by Q3. In Q4, MongoDB delivered $361.3M in revenue for 35.6% annual and 8.3% sequential growth. This beat the analyst estimate for $338M handily and even their own prior guidance for a range of $334M – $337M. Their prior guidance would have delivered 26% annual and 0.6% sequential growth, meaning that their actual beat brought about 8% of extra sequential growth.

While MongoDB outperformed their guidance nicely in Q4, the initial Q1 guide was a bit underwhelming. Analysts were looking for $352.6M for 23.6% annual growth and 4.3% above their Q4 estimate. MongoDB set Q1 guidance for a range of $344M-$348M for 21.3% annual growth. With the outperformance in Q4 generating $361M in revenue, the Q1 guide represents about a 4% sequential decrease or $15M at the midpoint. If MongoDB delivers a similar magnitude beat as they did in Q4 (about $24M), then they would reach $370M in revenue for about 2-3% sequential growth.

For the full year, the preliminary guide was weak as well. MongoDB expects revenue in a range of $1.480B – $1.510B, representing 16.4% growth over the actual FY2023 revenue of $1.284B. Analysts had expected $1.582B for 25.6% growth over their final estimate for FY2023 revenue. This is obviously a large miss relative to analyst expectations.

The big question is how conservative this full year guidance is. The sequential growth in Q1 gives one clue. If MongoDB only achieves 2-3% sequential growth each quarter through the full year, then revenue growth in the teens is realistic. On the other hand, if MongoDB were able to return to the sequential growth rates achieved last year as 2023 progresses, then the annual growth would push into the 20% range. An 8% sequential growth rate annualized represents growth of 36%.

Atlas revenue increased by 50% year/year in Q4, higher than the overall 36% growth rate for total revenue. This higher growth rate for Atlas is an important part of MongoDB’s investment thesis. Like other open core software models, MongoDB adds value in two ways. First, they layer proprietary features over the open source version of MongoDB. These improve security, scalability and management.

Second, with the cloud-hosted nature of Atlas, the customer doesn’t have to expend DevOps resources to manage their own MongoDB installation. While customers can choose to do management and hosting themselves by licensing the Enterprise Advanced (EA) version of the MongoDB software, Atlas handles all of this work for them. Having customers use the Atlas service generates a recurring revenue stream for MongoDB (although consumption based) and provides them with insight into customer usage patterns.

The Altas growth story makes MongoDB interesting as an investment. In Q4, Atlas made up 65% of total revenue or about $234.8M. In Q3, Atlas grew by 61% y/y and contributed 63% of revenue or $210.2M. That means on a sequential basis Atlas revenue grew by 11.7%, which was higher than the overall 8.3% sequential growth for Q4. The absolute dollar growth of $24.6M was the largest ever. As Atlas continues to contribute a large portion of overall revenue, its growth rate will determine the company’s total revenue growth.

While Atlas performance was relatively good, it underperformed management’s expectations. MongoDB generally benefits from a large increase in consumption in Q4, that provides a new baseline for growth the following year. This Q4 started off well in November, continuing the strong Atlas growth trends in Q3. The subsequent two months however experienced more of a drop off than expected. This was driven by less usage of customer applications over the Holidays. The pattern of lower usage reflected a broader macroeconomic slowdown, versus a specific customer segment or geo.

Consumption growth in February improved relative to December and January and was broadly in line with the average growth we’ve seen since the macro slowdown began in Q2 of last year. We continue to believe the recent fluctuations in consumption trends are largely driven by broad-based macroeconomic trends as they’re occurring across different geographies, vertical markets, and customer segments. Finally, retention rates remained incredibly strong in Q4, which exemplifies the value customers receive from MongoDB.

MongoDB Q4 FY2023 Earnings Call

In February, consumption growth improved as compared to the prior months. However, the baseline is lower, which is impacting the preliminary guidance for FY2024. While consumption growth in February has been better, it was still inline with the general slower usage experienced in 2022.

Like other software infrastructure companies, MongoDB is experiencing a similar dichotomy between existing customer usage and new customer adoption. The latter isn’t showing a slowdown. As I will discuss in the customer section, additions of Direct Sales customers (generally the larger ones), $100k and $1M customers remain at the top end of prior trends.

The challenge for MongoDB currently is the impact of existing large customer spend, which is not expanding as quickly as in the past. In some cases, it is contracting, as customer applications are experiencing less overall usage. This has been influenced previously by a drop off in business by some digital natives, like crypto exchanges (Coinbase) or food delivery (Instacart). This creates a negative headwind that exacerbates the slower expansion from mainstream customers.

Of course, as the macroeconomic backdrop stabilizes (or even improves), MongoDB’s consumption model can snap back quickly. They would benefit from the dual tailwinds of business growth by existing customers and then the contribution from the trail of new customers that are ramping up. Like with peers Snowflake and Datadog, the impact of a consumption model can cut both ways. As we transition into the second half of 2023 and 2024, this will be the pivot that investors should be monitoring for.

This change from macro headwinds to tailwinds could happen very quickly. The market will probably also front-run it. This anticipation may explain the price action in MDB since the earnings announcement. While the forward revenue guidance was disappointing, the stock is already trading higher than its pre-earnings announcement price on March 8th.

Profitability

After a couple of years of middling progress on profitability measures, MongoDB has demonstrated significant improvement in Non-GAAP operating and FCF margin over the last year. Like other software infrastructure companies, they have shifted away from a growth at all costs model to one where growth is balanced with progress on managing expenses. This has manifested most clearly on headcount, but also other areas where they are starting to realize operating leverage, including gross margins.

For Q4, MongoDB reported Non-GAAP gross margin of 77.7%, which was up almost 400 bps from 73.9% a year ago. Management once again attributed the gross margin improvement to increased efficiencies in the Atlas cloud offering. Greater scale provides opportunities for volume discounts and optimizations of hosting solutions on infrastructure provided by the hyperscalers. Non-GAAP gross profit increased by 42.6% year/year, which was higher than the 36% increase in revenue.

Non-GAAP income from operations nearly tripled year over year, increasing from $13.0M a year ago to $37.2M in Q4 of this year. This translates to an operating margin of 10.3%, representing a nice step up from 5.9% in Q3. Combined with Q4 revenue growth puts MongoDB comfortably into the Rule of 40. As part of their Q3 earnings report, management had set the Q4 target for Non-GAAP income from operations to be just $6M to $8M. On a per share basis, MongoDB delivered $0.57 Non-GAAP EPS in Q4. This crushed the analyst expectation for $0.07. In Q4 of the prior year, Non-GAAP EPS was $0.10.

Looking forward, management set a target for Q1 to deliver $10M – $13M in Non-GAAP operating income. This estimate is almost double the preliminary guide for Q4. This translates into Non-GAAP net income per share in a range of $0.17 – $0.20, which beat the analyst expectation for $0.13. Given the outperformance in Q4, we may see an actual result that is much higher than this.

For the full year, MongoDB provided a similarly optimistic projection on profitability. They expect to deliver Non-GAAP operating income in the range of $69M – $84M, which is above the $62M they delivered in the prior year. While this isn’t a large increase, investors should keep in mind the outperformance just delivered over the course of FY2023. As part of their Q4 FY2022 earnings report a year ago, the preliminary target for operating income was for a loss in the range of ($22M) to ($7M), as compared to the actual value of $62M.

On an EPS basis, leadership expects to deliver Non-GAAP net income per share in the range of $0.96 to $1.10, which is also above the $0.81 EPS just delivered. Going back a year, leadership had set the initial FY2023 target at ($0.51) to ($0.29), which they beat pretty significantly.

Looking at cash flow, MongoDB delivered FCF of $23.8M in Q4 (6.6% FCF margin), which was up 42% over the $16.8M in FCF generated in Q4 of FY2022. For the full year, FCF was negative ($24.7M) in FY2023, as compared to ($6.7M) in FY2022. Cash flow generation improved substantially in the second half of FY2023, and is likely to remain this way going forward. In Q3, FCF margin was -2.5% and was even worse in Q2 at -16%. It’s nice to see the rapid improvement in cash flow margin.

All in, MongoDB has $1.8 billion in cash, cash equivalents, short-term investments and restricted cash, providing a comfortable reserve for targeted acquisitions if needed.

Staffing

The 10-K provided some insight into hiring trends. I created the following chart of total employee counts and included those attributed to Sales and Marketing from the quarterly data. 

Headcount for the period ending on January 31, 2023 provides insight into the source of cost savings and increased profitability measures. In Q4, MongoDB only increased overall headcount by 1.9% or 85 employees. This represents a pretty substantial slowdown from the 6-12% increases quarterly over the past two years. In Q2, they did surge hiring above prior quarterly growth rates, providing some cushion for the current period reduction.

The staffing decrease was most noticeable in Sales and Marketing in Q4, where headcount actually decreased q/q. While MongoDB did not perform an actual layoff, they obviously paused hiring and didn’t backfill the 27 team members who either left the company or were managed out. A reduction in sales staff will be important to monitor going forward, as that could impact revenue growth several quarters out. Fortunately, MongoDB almost doubled the rate of hiring in S&M in Q2, which provides some buffer for the reduction in Q4.

In the prepared remarks, MongoDB’s CEO stated that they intend to slow headcount growth from 30% in FY2023 to the “single digits” in FY2024. If the macro environment and demand picks back up later this year, I could see hiring reaccelerate. In the meantime, MongoDB has built up some cushion in staffing levels and should be able to more than execute on their financial goals with the planned organization.

Customer Activity

Like other software infrastructure peers, MongoDB is experiencing decelerating revenue growth, while customer activity remains relatively strong. This is explained by a slowdown (or even reduction in some cases) of spend by large existing customers that ramped up usage quickly during the Covid-fueled rush towards digital transformation. As those companies have been hit with economic headwinds, they have looked for ways to optimize their existing usage and place more checks on expansion projects.

This slowdown in spend from existing customers is being counteracted by a steady increase in new customers moving onto the MongoDB platform. While the slowdown in existing spend is causing noticeable revenue growth deceleration, the broader secular trends of cloud migration and digital transformation appear to be intact. A thesis that cloud migration has stalled or become saturated would be supported if total or large customer counts flatlined. Yet, we aren’t seeing this trend with the software companies that report customer counts. As the hyperscalers don’t provide customer data, it is easier for investors to conclude that cloud migration has stalled significantly.

For MongoDB, they reported 40,800 total customers in Q4, which is up 1,700 sequentially from 39,100 in Q3. Over the past year, MongoDB had been adding about 1,800 to 2,200 customers per quarter, so the Q4 additions are just slightly lower than the historical range. Nonetheless, this represents a healthy increase in a tough environment. With over 40,000 total customers, MongoDB enjoys a large base to grow into larger spend.

For customers that MongoDB expects to grow substantially over time, they assign the “Direct Sales” label. As opposed to the self-serve mode that the majority of customers are relegated to, a Direct Sales customer is assigned a salesperson. That salesperson is incentivized to work closely with the customer to learn their business and identify new workloads that would be appropriate to move onto the MongoDB platform. Growth in Direct Sales customers provides an indicator of future growth potential for customers with large spend.

In Q4, MongoDB added 500 Direct Sales customers, bringing the total to 6,400. This category of customers is growing faster than total customers, with 46% annual and 8.5% sequential growth in Q4. In Q3, MongoDB added 500 Direct Sales customers as well. In the prior year, the range has been 400 to 600 new Direct Sales customers each quarter.

Direct Sales customers generated 88% of total subscription revenue in Q4. This is a new high, up from 87% in Q3 and 83% to 87% in the two years prior. This growth demonstrates that MongoDB’s focus on Direct Sales customers is working and makes this an important customer segment.

Another objective measure for large customers is those spending $100k or more in ARR. In Q4, that count increased by 106 over the prior quarter. This represents an increase over the 83 large customers added in Q3. It also ties the record of 106 additions in Q4 FY2022. On an annual basis, MongoDB publishes the number of $1M+ customers. At the end of FY2023, they reported 213 of these, up from 164 a year ago for about 30% growth.

MongoDB leadership also reported their net annual revenue expansion (like NRR) rate was above 120% for the quarter. This implies that customers over a year old increased their spend by 20% or more when comparing the prior period with the same a year ago.

As MongoDB has passed 40,000 paying customers, the rate of customer additions is still relatively strong at 24% annually. Combined with their net expansion rate, this should support healthy revenue growth going forward. More importantly, with about 4% of customers spending more than $100k a year, the bigger opportunity for MongoDB is in spend expansion for existing customers.

Customer Examples

In the prepared remarks, MongoDB’s CEO highlighted several examples of customer activity. These align with broader themes around platform consolidation and the usefulness of MongoDB’s offering.

• Telefonica. Selected MongoDB as the database platform for their fleet of 30M IoT devices that run on their managed connectivity service. This move reduced the cost of their prior solution by 40%.
• Iron Mountain. Adopted MongoDB to support the expansion from providing traditional physical asset storage and shredding solutions into offering an intelligent document processing solution. They use MongoDB to store and search tens of millions of customer documents.
• Penske. Selected MongoDB Atlas to modernize its customer notification platform, that had been built on a relational database. The MongoDB document data model increased developer productivity. Further, MongoDB’s clustering technology supported greater scalability and smoothed out performance slowdowns from traffic spikes.
• Two of Europe’s Largest Retailers. Are replacing a myriad of legacy and niche database solutions with Atlas Search and Atlas Device Sync. This falls under the broader theme of platform consolidation to reduce operating costs and simplify infrastructure.
• Two Global Financial Institutions. Are preparing to deploy hundreds of new and existing applications onto Atlas over the next few quarters. Both companies chose to standardize on MongoDB, after evaluating alternatives from other vendors and the hyperscalers.

In several of these examples, the customer is using MongoDB as a generalized data platform upon which any development team in the organization can build an application. This “platform” configuration provides a powerful expansion motion for usage, as each new application will have a separate MongoDB cluster provisioned.

Interfacing with these larger customers to help evangelize the suitability of MongoDB for additional workloads is the function of the Direct Sales team. With the assistance of sales engineers, they can engage with the customer’s engineering leadership to point out additional MongoDB use cases, like search, times series (for IoT), real-time analytics and mobile. They can also work with the team to migrate existing relational schemas to a document-oriented equivalent.

Another motion being captured by MongoDB is the consolidation of database vendors. A number of customer examples over the past couple of quarters have highlighted cost savings realized by moving to MongoDB Atlas, either by reducing license fees from multiple alternate solutions or decreasing staffing support required to maintain open source projects. This represents a new marketing message, reflecting the benefits of consolidating multiple application workloads onto the MongoDB platform. This aligns with messaging from other software infrastructure providers in recent quarters and plays well with overall enterprise sentiment given the macro environment.

Investment Plan (and a word on AI)

While I am hesitant to point to AI as a potential growth driver for MongoDB, it may well be. At the Morgan Stanley TMT conference, MongoDB’s CEO described how AI could represent “a real accelerant” for their business. He referenced three potential drivers for increased usage of MongoDB:

• New software applications. As AI models proliferate, new companies will emerge that create Internet-based experiences that leverage AI. These companies will require transactional databases to serve as an intermediate store for their data, interfacing directly with the application. As a document store, MongoDB is ideally suited for this function. Just look at this sample list of hundreds of AI-enabled applications from The Rundown. These are all delivered over the Internet and will require the same software infrastructure support for security, delivery, monitoring and operational data as standard applications.
• Higher Developer Productivity. As AI-powered coding assistants proliferate, developers will be able to complete development work faster. This will result in more applications. Teams will quickly crank through their enterprise’s digital transformation project list. In the future, fewer developers will be needed to accomplish the same amount of work, freeing up IT budget to pay for more software infrastructure to host all these applications.
• Enterprise AI Use Cases. As enterprises realize that they have unique, proprietary data sets that could be loaded into AI models, they will rush to upgrade their database infrastructure to more modern solutions to improve accessibility. This should drive new workloads and customer wins towards MongoDB, as these enterprises accelerate their transition off of legacy data stores and relational models.

As the AI space is moving so quickly, I even missed the fact that MongoDB cited popular AI community service Hugging Face as a customer on the Q3 earnings call. Leadership has mentioned other AI providers as new customers. As these companies are growing rapidly and enjoying a seemingly unending stream of VC investment, this could provide a new source of growth for MongoDB.

Hugging Face, a fast-growing AI company, migrated from MongoDB Community to MongoDB Atlas to scale their open-source platform and online community for machine learning. The company’s shift to Atlas allowed them to rely on our developer data platform for software and security compliance, take advantage of change streams to speed decision-making, simplify the infrastructure through a single control plane for managing data, and reduce time spent on maintenance through Atlas’ integrated services.

MonGoDB Q3 FY2023 Earnings Call

Because AI systems need large amounts of data to feed their models, MongoDB’s support for unstructured data might provide a key ingredient. As more applications are built to leverage new AI-driven insights, they will require data storage. MongoDB provides an ideal, multi-purpose data store to handle all of the application plumbing that surrounds the AI engine.

Outside of AI use cases, MongoDB is still popular among developers for standard enterprise digital transformation projects. Third-party analyst firms issued positive reviews of the MongoDB platform over the past 6 months, placing their solution at the high-end of rankings relative to competitive offerings. MongoDB made its debut onto the Gartner Magic Quadrant for DBMS in the Leaders Quadrant, which is a rare achievement for a newcomer. Similarly, Forrester ranked MongoDB as a Leader among 15 competitive providers in the modern Translytical Data Platform category. These reports from Gartner and Forrester are often used by CIOs to make purchase decisions.

While the initial revenue growth outlook for FY2024 is disappointing, I think it is conservative. If the macro environment improves and enterprise IT investments pick up again, MongoDB will benefit from the combination of renewed customer application usage and new workload migrations. Additionally, their customer growth continued on the same trajectory. These new workloads will grow usage, layering on consumption to the recovery of existing customer spend.

The highlight of the Q4 report was the significant improvement in profitability measures. MongoDB achieved record operating margin and significant gross margin improvement. They are comfortably above the Rule of 40, in spite of revenue deceleration. Their operating leverage appears poised to continue into FY2024, as preliminary projections for operating margin start at the top of the prior year’s range.

Looking at valuation, MDB has a P/S ratio of 12.5 currently for 36% annual growth and positive Non-GAAP operating income. This is down from the 15-20x range in 2022. Pre-Covid, this ratio was also above 15x, with higher revenue growth but worse operating margin. It’s notable that MongoDB has been publicly traded longer than other software infrastructure companies that I cover. Their quarterly revenue has increased almost 10x since their IPO in October 2017. This speaks to the durability of their growth beyond the surge experienced during Covid.

Analysts currently estimate that MongoDB will finish this year (FY2024) with $1.507B in revenue, which represents 17.4% growth over the prior year. For next year (FY2025), they have modeled just $1.836B for 21.8% growth, reflecting the anticipation of some reacceleration coming out of 2023.

While the macro environment introduces a wildcard, I think that MongoDB can beat these estimates. I would point to the large expansion opportunity with existing customers, continued healthy growth in new customer additions and the potential for AI to inject new application use cases into the market. With a targeted TAM of $109B by the end of 2024, MongoDB’s penetration would be about 2% of the market at that point.

I currently have a 12% allocation to MDB in my portfolio. I don’t plan to make any changes at this point. Relative to other software infrastructure stocks, I think MongoDB is well positioned as enterprises appear willing to continue their investments in the platform. Any change in the macro environment and associated pressure on IT budgets over the next year should generate new tailwinds for MongoDB and other software infrastructure providers. Over the long term, I see a long runway for MongoDB to grow their revenue, similar to the trajectory they have enjoyed over the 5 years since going public.

Further Reading

• Our partners at Cestrian Capital Research cover MongoDB as part of their Cestrian Tech Select newsletter, which includes a broad range of technology companies with a deep focus on financial and chart analysis. They recently published a review of MongoDB’s Q4 results, that provides a useful supplement to my coverage.

NOTE: This article does not represent investment advice and is solely the author’s opinion for managing his own investment portfolio. Readers are expected to perform their own due diligence before making investment decisions. Please see the Disclaimer for more detail.