MongoDB (MDB) Q4 2020 Earnings Teardown

“I believe we will look back at 2020 as the year that put an exclamation point on the need for businesses to reinvent themselves using software and data” - Dev Ittycheria, MDB earnings call Q4 2020

Summary

$171M Revenue (+38% YoY)
Subscription Revenue $163.9M (+39% YoY)
Atlas revenue (+66% YoY), now representing 49% of revenue
Atlas has over 23,300 customers, adding 7900 over the past year
24,800 customers (2,200 net new in Q4 and 17,000 added in 2020)
Net AR expansion rate was above 120%
975 customers with at least $100,000 in ARR and annualized MRR, up from 751 a year ago

Company Background

MongoDB is an open-source NoSQL (“Not only SQL”) database. MongoDB was designed to be a general purpose, document-based, distributed database built for modern application developers and for the cloud era. The platform enables developers to build and modernize applications rapidly and cost-effectively across a broad range of use cases.

Databases are at the heart of applications. If the database has performance or scaling issues, both the application and the business that invested in it suffer. Therefore, selecting databases is one of the most important decisions for dev teams.

MongoDB built an easy-to-use database that's applicable for almost every conceivable use case, and engineered for mission-critical workloads. The foundation of MongoDB’s database is a document model, which maps to the way developers think and code and has shown to be the most productive way for developers to work with data. MongoDB’s database was built from the ground up with a distributed architecture, allowing applications to scale more easily and cost-effectively while delivering outstanding performance.

Relational databases were popular because they handled storage requirements more efficiently. However, over the last 50 years storage has no longer been a constraint in many organizations as storage has become commoditized.

In a relational data world, data was organized by rows and columns of a table, the analog in a nonrelational world is that a document is represented by a row, and a collection is represented by a column - so when database admins and IT architects are thinking about their enterprise, they can go back and forth and do this code switching. It enables their downstream developers to better leverage the data more intuitively.

Over the course of time, alternative technologies have tried to replace relational databases, but they all failed because of a lack of developer adoption. The founders of MongoDB were developers themselves and intimately understood the challenges that developers faced working with relational databases, especially since the tablet approach bore little resemblance to how data is represented in application code, consequently making relational databases hard to use.

The way that applications were built over the last 40 years and the way that applications sat on top of relational databases has now become non intuitive for developers to use. Data is spread around documents, social media, complex web apps, IoT, etc. so traditional SQL databases can’t handle these data due to the continuous changing behavior. Traditional databases need to know the shape of the data beforehand to store those, and thus, it failed to capture continuous evolving data. MongoDB’s data model is really the reason it's won over developers and how MongoDB established its brand equity in the market, making it easy for them to scale initial lands into larger enterprise deals.

Due to its ease of use and flexibility, the document model garnered incredible developer enthusiasm. By every objective measure, MongoDB is the most popular modern database in the world today. The MongoDB community of developers is large and global and continues to grow every day.

MongoDB utilizes the document-based NoSQL database which is the most natural configuration among NoSQL databases as documents can be stored and retrieved in a form much closer to the data objects used in applications. For example, take a patient medical record. In a typical SQL database the patient’s name would go in one table, the patient’s address would go in another table, and the patient’s phone number would go in another table. Implementing a document SQL database would store all related patient information in one file thus reducing development complexity. A key-value based NoSQL database is the simplest implementation of NoSQL and can be thought of as a relational database with only two columns: the key (or attribute name) and the value. Using a simplified version of our patient example, the key would represent an abstraction of patient names and the value would be a specific patient's name. In a column-based NoSQL database, data is organized in a set of columns rather than rows. This results in high performance on aggregation queries as the data is read in columns directly without consuming memory with the unwanted data. The last type of NoSQL database is the graph database which emphasizes the relationship between data elements. Each element is stored in a node and each connection between nodes is called a relationship or link. Compared to a relational database where tables are linked implicitly, a graph database is multi-relational in nature.

Product Overview

Atlas, MongoDB’s flagship product, is the simplest and most effective method to run MongoDB in the cloud. The Atlas platform offers the simplicity of a fully managed SaaS offering with the security and latency optimization of on-prem database solutions. Imagine creating a MongoDB server with a click of a button that runs on your virtual private cloud and in the same region as your data. Atlas eliminates the operational complexities of deploying and scaling databases by eliminating arduous tasks like database configuration, infrastructure provisioning, scaling, patching, and backups.

MongoDB Enterprise Advanced is the best way to run MongoDB on your own infrastructure and servers. The software suite includes advanced support, analytics (monitoring, automation, backup), and security features over the open-source community edition.

MongoDB continues to ship out products at an incredible rate to prove its platform is durable and can stand alone and compete against the major cloud vendors.

Multi document - ACID transaction support that works across distributed clusters
Field-level data encryption - a major enhancement for security and privacy compliance
Data Lake – Expands the use of MongoDB into general data warehousing use cases
Full-Text Search – Supports full-text search as part of the standard query language
Charts – allows users to create data visualizations and share them with their teams without requiring code
Realm - enables developers to build very sophisticated mobile applications and synchronize the data at the edge with data at the core. That saves developers an enormous amount of time and effort, and it's something that's quite complicated.

Business Model

MongoDB pioneered the freemium model in software, charging for Atlas instances on a per server hour basis and then charging for ancillary products such as data transfer or backup on a per GB basis.

Why MongoDB wins:

Multi Cloud: Organizations shifting to multi cloud strategies has been a well-known recent trend. Running an application across multiple clouds has a number of benefits. The application is more resilient as it is not subject to single cloud outages, developers can easily leverage the unique capabilities of each cloud provider, and the applications can migrate between clouds with no downtime, avoiding vendor lock-in. Atlas is the first global cloud database that delivers a true multi-cloud solution. Apps built on MongoDB can run on-premise, on any cloud, or across different cloud providers, which offers real platform independence, benefits no other alternative can provide. A CTO from a Fortune 100 business almost fell off his chair when we demonstrated how easily a customer can deploy workload across two different cloud providers. He remarked he was planning to have a 50-person team work on this, and now, one person can do this in a few hours. Platform independence is something the C-suite, in particular, cares a lot about.
MongoDB’s multi cloud compatibility provides platform independence: Platform independence is something that customers, specifically C-suites, care a lot about. When MongoDB showcases their product to customers, they give demos for customers and show them that literally with a few clicks in a few minutes, they can provision clusters across two or more different cloud providers and do it very, very easily.
Breadth of developer mindshare: MongoDB was built as the database for modern developers. There's strong virality of MongoDB in the market because its open source and free to use. Developers can go to mongodb.com, download the database tools they need and start coding. As organizations have begun to ask their developers, the developers are increasingly becoming the decision makers in the company.
Product: MongoDB is the de facto database when speed and horizontal scalability are very important. MongoDB is also pretty good for unstructured or irregularly structured data that’s hard to write a schema for. Popular use cases for using MongoDB include: web scraping or data ingestion from APIs. Similarly, consumer apps/games where occasional data loss or inconsistency isn’t a big deal. It can also be used effectively as a kind of durable cache (with a nice query language) if you provide sufficient RAM. While its guarantees or lack thereof aren’t great for a database, they’re pretty good for a cache.

Market Opportunity

Database spend is estimated to be ~$65B today and the market is estimated to grow to somewhere near $100 billion, right, just in terms of spend on databases. Most of this spend is directed to relational databases. However, NoSQL as a whole is growing. But in addition, the entire database market is growing as well.

MongoDB benefits from two massive tailwinds: 1) the database market, in general, is expanding. The proliferation of software and the needs of organizations around their data is more important than ever.

2) The NoSQL market in general, as MongoDB as well as other NoSQL vendors continue to see value in using a document-based data model, and that subsector of that entire database spend is going to increase as well as it takes greater market share.

Key Takeaways

1. MongoDB continues to demonstrate the importance of maximizing your developer.

COVID-19 accelerated the pace of adoption for organizations to be digital-first as software has become a source of competitive differentiation. There's simply no off-the-shelf software that organizations can buy to differentiate themselves against their competition. Organizations are realizing that they cannot buy a competitive advantage, they have to build it themselves.
Managing data is a developer's most challenging problem and the biggest drain on their productivity. Legacy platforms are not designed for how developers think and code, nor they're designed for performance and scale. This problem only gets worse as the data intensity and performance requirements of modern applications increase.
Developers spend an inordinate amount of time working around the limitations of existing solutions versus spending time building better applications and user experiences that drive a competitive advantage. Moving to the cloud held out the promise of reduced complexity and improved productivity. What many early cloud adopters have learned the hard way is that moving to the cloud often exacerbates the poor state of their data infrastructure.
Single-purpose databases are on the wrong side of change: given the known limitations of relational databases, cloud providers promote a number of other single-purpose databases to address more diverse requirements which, in turn, create a larger number of data stores for customers to learn, manage and integrate. This dramatically increases the complexity of customers’ data architecture. Moreover, cloud providers encourage customers to go all-in with their proprietary offerings across the IT stack. The overwhelming number of proprietary point solutions not only slows developers down but also deepens cloud vendor lock-in.
Given the failings of existing approaches, developers and enterprises are clamoring for a modern application data platform that accelerates innovation. To be effective, a modern platform must support a broad range of use cases, meet stringent requirements for resiliency, security and scalability and provide enterprises the flexibility to run applications wherever they want.
Developers view MongoDB as a very attractive platform because they will never have to rewrite the application as they transition from on-prem to the cloud or from one cloud provider to another cloud provider, which makes it a very attractive future-proof platform for customers.

2. Customer growth is inflecting, and there's likely a long tail of growth from these cohorts

Year-over-year customer growth has been inflecting over the past 5 quarters, more dramatically seen in the Atlas customer numbers.

The cost to acquire net new customers is going down...

However, ARPU has also been on the decline, implying that the new customers are still very early in their database journey and have plenty of room to expand.

Management noted that they usually land an account by identifying a specific pain point that cannot be addressed by existing technologies and the expansions can last a very long time as customers continue to build upon MongoDB’s platform.

Customer example given:

“In a Fortune 50 financial institution that is now a seven-figure customer, MongoDB’s early use cases leveraged the strength of the document model to efficiently capture complex loan applications with hundreds of entries. In the case of a global gaming leader, developers first started using MongoDB for microservices that leverage the rapid scalability of MDB’s technology. After establishing a presence with the customer, they leverage the success of the initial workloads to expand across divisional and geographic boundaries within the account. A top 10 U.S.bank experienced a major data center outage a couple of years ago, and MongoDB outperformed all other databases in terms of performance and availability. At the time, MongoDB seized on the performance of their platform to more broadly serve customers' needs, organizing teachings and hackathons with other app development teams across the company. Two years later, that bank's customers' website experience runs on MongoDB, and with other use cases, the bank is now an eight-figure -- annual eight-figure customer. Depending on the size of the account, the expansion phase can last many years.” - Dev Ittycheria

Moreover, MongoDB believes they’re only at the beginning stages of becoming enterprise standard. Even within their largest customers, MongoDB typically represents a small fraction of their total database spend, affording the opportunity to meaningfully grow even in their biggest accounts.

MongoDB’s product has excellent retention as they reported greater than 120% net expansion rate in Q4, because it’s not a product that you just buy and then start using, customers have to actually build an application on top of it. So there's a certain rate and pace of app development, whether you're building new applications or replatforming existing applications. Once MongoDB gets into an account, they’ve found it reasonably easy to expand into adjacent opportunities and the adjacent opportunities tend to be bigger than the initial deal.

Cohort expansion is returning to pre-pandemic levels:

“we've seen in terms of the Atlas cohorts is a resumption of the pre-COVID cohort behavior, so it's really more about new business, and it's very consistent with what we talked about last quarter, which is sort of bigger deals, multi year deals, getting extra scrutiny, that kind of stuff”

So with regard to large customers, most of MongoDB’s large customers start as small customers.

That's typically because they have one use case of one workload that grows very, very fast. But in most situations, it's customers adding more workloads to the MongoDB platform. Depending on the size of the account, it could be multiple years as we are in the expansion phase of winning more and more business.

And that, at some point in time, when you start talking to senior-level stakeholders, they see how popular we are with their developers, they see how widely spread we are across the organization, and they want to build a more strategic relationship. And for us, we want to be declared a standard where, by definition, a developer doesn't have to seek permission to use MongoDB. So it's really a function of leveraging our successes early on, proving out the scalability and flexibility of our platform. And then really showing them that MongoDB can be truly a versatile application data platform, not just for on-premise but across all the major cloud providers as well.

3. MongoDB is on the right side of change: “lift & shift is not the right approach”

Digitalization trends catalyzed the narrative of a secular shift to the cloud. This meant moving relational workloads from on-prem solutions into the cloud to leverage the power of its compute, storage, and networking abilities. The most common go-to-market tactic cloud vendors use is “lift and shift”, the process of moving on-prem relational workloads to an open-source relational database service, such as Postgres. But what's happening is that people are recognizing that just lift and shift is not the right approach because companies are just replicating the same, existing on-premise problems in the cloud..

After using this approach for a number of workloads, customers soon realize that the expected cost benefits from a cloud deployment are more than offset by the limitation of the underlying architectural constraints of relational databases.Thus, “lift and shift” is not the same as modernization. And customers are increasingly coming to appreciate the distinction between the two.

Rather than “lift and shift” to move workloads, what companies need in the modern age is lift and transform, and that's where MongoDB comes in. Customers increasingly recognize the benefits of a flexible data model through the document model. Running and using multiple use cases is more beneficial because of the versatility of the document model. They also appreciate the scalability and performance of our distributed architecture and it's even more pronounced because Atlas can automate those processes.

Management noted that a senior IT executive in one of the world's largest asset management firms recently told them, "He doesn't know of a single one of his peers who didn't come to regret the lift and shift strategy." Second, given the known limitations of relational databases, cloud providers promoted a number of other single-purpose databases to address more diverse requirements which, in turn, create a larger number of data stores for customers to learn, manage and integrate. This dramatically increases the complexity of their data architecture. Third, cloud providers encourage customers to go all-in with their proprietary offerings across the IT stack. The overwhelming number of proprietary point solutions not only slows developers down but also deepens cloud vendor lock-in.

4. MongoDB continues to show durable platform creation that allows it to standalone vs the major clouds

Defensibility against the major cloud providers matters a ton among software stocks because unless a company can distinguish itself, it becomes commoditized by AWS/Azure/GCP who can win off distribution. Software stocks trade at such high multiples because investors are paying for durability, and durability gives investors confidence that the software company can come close to its potential steady state margins.

Management highlighted that they’re “starting to see vertical-specific, deep-in-the-back-office ISVs in financial services, insurance, in telecom, etc., who are looking to replatform. And so we actually have a small team focused on the ISVs. And there, it's almost like a two-step process where we are essentially selling to the CTOs, the VP of product, sometimes the CEO, depending on the size of the ISV, and then helping them build or replatform their product on MongoDB and then helping them generate the first set of customers.”

They cited customer buying behavior was changing as customers want to consume SaaS and ISVs want to stop paying the Oracle tax and ISVs are attracted to the flexibility and agility of the document model, as well as the scalability of MongoDB’s architecture, so it allows them to serve global needs quite easily.

Management also added that ISVs typically don't want to use a cloud proprietary database because, by definition, that will limit them to only one cloud, and customers care about multi-cloud. And so the fact that MongoDB runs across all the major cloud vendors and the fact that they can offer capabilities in a multi-cloud environment makes MongoDB even that much more attractive.

Valuation

Today, MongoDB is a $17B company that trades at 24.5x ARR doing 683M in ARR (growing 38% YoY).

Despite growing topline at a remarkable pace over the past few years, MongoDB’s path to profitability has been murky. The company is still aggressively growing as it aims to build upon its developer mindshare and continue to ship out products at a rapid pace.Moreover, in its freemium business model, gross margins can be accretive as they continue to move upmarket and monetize a greater share of their users. Similarly, its low friction self-serve GTM could result in structurally lower sales spend. Thus, despite having -10% FCF margin and high payback period in the short term, it's likely they will see greater sales efficiency as revenues from existing cohorts continue to expand in the near future.

The company’s EV/NTM multiple (currently 22.1x) has fallen from February highs of 34.2x and averaged around 17-18x over the past three years. However, I’d argue that because of MongoDB’s durability, mission criticality, and competitive positioning in one of the largest software TAMs - it should be trading closer to peers like OKTA (31x ARR) who’ve shown comparable growth levels and similar steady state margin profile to MDB.

Concluding thoughts

The challenge with software businesses is that what’s hot now may not necessarily be true in 5 years; thus, investors are willing to pay incredible multiples for durability. MongoDB’s durability comes from the fact that 1) it's a true multi cloud story, especially in the enterprise; 2) it has ubiquitous organic developer adoption; 3) the breadth of features Atlas addresses for MDB to win this massive TAM and compete amongst AWS, Azure, and GCP.

MongoDB’s founders Dwight Merriman, Kevin Ryan, and Eliot Horowitz recognized the technological advantages of document-based databases as opposed to traditional relational ones. As such, MongoDB was built for the modern developer; and for developer-focused products, developer mindshare and satisfaction created the flywheel.