MDB - MongoDB: Document Based Database Transformation Empowered By AI And Big Data

2023-08-23 05:30:38 ET

Summary

• MongoDB's document-based database structure is better suited for the demands of the AI and big data era, offering flexibility and scalability at a lower cost.
• The global database market is projected to reach $203.6 billion by 2027, with MongoDB well-positioned to benefit from the migration to new structured databases.
• The growth of MongoDB is closely tied to the surge in application development, driven by low-code development and the increasing need for new structured databases.

MongoDB ( MDB ) is a document-based database provider. The global database landscape is currently dominated by legacy relational databases such as Oracle ( ORCL ), SQL Server, and DB2, which were designed decades ago. Document-based databases are part of the NoSQL structure, and I believe this new database structure is better suited to the demands of the emerging AI and big data era. It offers greater flexibility and scalability at a much lower cost. I envision MongoDB gaining a more significant foothold in the expansive database management market, with significant growth potential ahead.

Rational Database versus Document-Based Database

To understand MongoDB's business, it is essential to grasp the distinctions between traditional relational databases and document-based databases.

All these existing relational databases were designed decades ago, and they utilize rigid rows and columns to store data. In these databases, every record must adhere to the same structure or fields. For instance, suppose you have one table that records basic employee information, such as first name, last name, gender, age, and ID. If you wish to include information about each employee's hobbies, you need to create another table to accommodate multiple hobbies for each employee, linking the two tables via employee ID.

In contrast, a document-based database offers several advantages over a relational database:

Flexibility : Document-based databases do not rely on rows and columns, providing the capability to manage both structured and unstructured data. Using the same employee example, a document-based database can store all employee information in a single document, encompassing basic details and multiple hobbies. Records do not need to adhere to a rigid structure; instead, hobbies information can be stored within a single field in each employee's record document. This simplifies database management for administrators and facilitates future record revisions. Moreover, since there are no connections between different documents, making changes to any document is straightforward, offering superior flexibility for enterprises.

Scalability : Expanding a relational database necessitates adding more database hardware and purchasing additional software licenses, resulting in significant costs. Document-based databases, on the other hand, store data in various documents, allowing for distribution across multiple servers or server clusters. Document-based databases offer cost-effective scalability.

Massive Data Processing : When applications require processing massive datasets with varying structures, document-based databases prove more suitable. They can store both structured and unstructured data. For instance, a large machine learning algorithm may require vast datasets from diverse sources, including server logs, website visit records, and social media data, all of which may have dissimilar data structures. A document-based database can support this type of data processing.

In summary, MongoDB's document-based database is better suited for big data processing, offering greater flexibility and scalability compared to traditional relational database technologies.

Market Growth Potential

According to Gartner's report published on August 2nd 2023, the global database market is projected to experience a compound annual growth rate of 16.8% from 2022 to 2027, reaching a total value of $203.6 billion by 2027. Currently, the NoSQL database sector holds a relatively small market share, with legacy relational databases dominating the market.

As MongoDB's management indicated, migrating from a traditional database to a new structured database is a time-consuming process, as it necessitates rewriting application code and then migrating the database. Consequently, the majority of NoSQL database growth is currently driven by new workloads and applications. MongoDB has recently introduced its Relational Migrator tool, which enables enterprises to migrate data from legacy vendors to MongoDB. Additionally, the tool can assist in generating sample code for data queries. This tool is expected to expedite the migration of legacy systems for enterprises. Once the migration is complete and enterprises transition to a new structured database, they are likely to experience cost savings and modernize their data structures.

If MongoDB can increasingly replace traditional databases, it stands to benefit from both the growth in new workloads and the substitution of existing workloads.

Low-Code Speeds up Application Creation

The growth of MongoDB is closely linked to the number of new applications developed, as each application necessitates a database. Therefore, as more applications are created, there is a higher demand for MongoDB's databases. The emergence of generative AI technology is making low-code development a reality, as AI can automatically generate substantial portions of code for engineers.

According to Microsoft's forecast , the next five years are expected to witness the creation of 500 million more applications, surpassing the total number built in the past 40 years. Moreover, modern applications increasingly require new structured databases like MongoDB, particularly as these applications often incorporate AI functionalities and process unstructured datasets. MongoDB's document-based databases empower engineers to write code in a manner that aligns with how data is stored in the database. Consequently, I believe MongoDB stands to gain significantly from the surge in application development anticipated over the next five years.

Growth Driven by AI and Big Data

I firmly believe that the most critical factor for AI and machine learning is the availability of high-quality datasets, especially when it comes to large algorithmic machine learning models that require vast volumes of data. Additionally, the foundation of data analytics and big data lies in the utilization of unique, unstructured data. Consequently, I am highly optimistic about MongoDB's growth potential, driven by the ongoing trends in AI and big data.

Furthermore, I see AI and Big Data adoption as catalysts for accelerating cloud migration and application modernization. To engage in AI and machine learning, enterprises are compelled to shift their workloads to the cloud. Simultaneously, they must redesign their existing applications to harness the capabilities of AI technologies. These types of application modernization efforts present MongoDB with substantial growth opportunities.

Recent Financial Results and Outlook

On June 1, 2023, MongoDB announced its Q1 FY24 earnings, showcasing robust growth figures. Their revenue surged by 29% year-over-year, while adjusted gross profits saw an impressive increase of 30.6%. Furthermore, the total number of their customers grew by 22.4% compared to the previous year.

Looking forward, MongoDB has provided guidance for FY24, projecting a revenue growth rate of 18.5% to 20% and anticipating non-GAAP income from operations within the range of $110 million to $125 million.

In my assessment, their revenue guidance for FY24 appears rather conservative, taking into account the potential deceleration in database consumption resulting from macroeconomic factors.

Risk Assessment

Competitions : I believe MongoDB faces competition from two primary categories: legacy vendors and emerging NoSQL databases. Legacy vendors may have difficulty introducing disruptive technologies that could jeopardize their established revenue streams, so they pose less concern. In contrast, the landscape includes numerous new NoSQL databases like Couchbase ( BASE ) and Astra DB . MongoDB enjoys a first-mover advantage and maintains a robust growth trajectory. For instance, in Q1 FY24 , MongoDB witnessed a remarkable 28% year-over-year growth in its six-figure customer count, underscoring its strong market presence.

Macro Uncertainties: I believe this is a common risk shared by cloud-based software companies. During periods of macroeconomic uncertainty, enterprises often consider reducing or postponing their cloud investments and projects, which could, in turn, impact application usage. MongoDB's revenue model is consumption-based, and any deceleration in the consumption of existing customers could potentially dampen their revenue growth.

However, it's worth noting that MongoDB's full-year guidance may already factor in the potential slowdown in consumption.

Negative Profitability : MongoDB is currently in the early investment stage and has not yet generated profits. Many enterprises are likely to begin adopting MongoDB's products for non-mission-critical workloads. As they become more familiar with MongoDB's technologies and experience their benefits, I believe these enterprises will gradually increase their usage of existing applications or extend MongoDB's products to a broader range of applications.

As previously mentioned, the entire NoSQL database sector is still in its infancy, with relational databases continuing to dominate the market. This suggests that MongoDB and similar NoSQL databases have ample room for growth and market expansion.

Valuations

I am using a DCF model to estimate the fair value of MongoDB. My assumptions include a 21% revenue growth rate in FY24, and I anticipate that MongoDB could become a company with revenue exceeding $13 billion by FY33. On the margin side, I expect gradual margin expansion, aiming for a 30% margin by FY33, which is a typical figure for most software companies.

With these assumptions, the model forecasts a free cash flow margin of 45.2% in FY33. The working capital as a percentage of revenue is maintained at a stable 24% according to my estimates.

To calculate the discount rate, I am using the following assumptions:

Beta: 1.12. Data Source: Yahoo Finance 5-year monthly data.

Risk-Free Rate of Return: 4%. I am using 10-year US government bond yield .

Expected Market Return Premium: 7%. I am using the same assumption across my models.

Cost of debt: 10%. I am using the same assumption across my models.

Equity/(Equity + Gross Debt): 42.4% using my projected figure in FY24.

As a results, the discount rate is estimated to be 9.6% in my model, and applying the WACC, the fair value of equity value is estimated to be $33 billion for MongoDB. As such, the fair value is $460 per share as per my estimates.

Final Thoughts

I believe MongoDB's document-based database technology has the potential to revolutionize the entire database industry, and their growth is driven by the increasing adoption of AI and big data technologies. In my view, MongoDB is positioned as a high-growth company for the next decade. Taking valuation into consideration, I would assign a 'Strong Buy' rating to MongoDB.

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