MongoDB Enhances Developer Data Platform

Despite all the interest in artificial intelligence (AI) and generative AI (GenAI), ISG’s Buyers Guide for Data Platforms serves as a reminder of the ongoing importance of product experience functionality to address adaptability, manageability, reliability and usability. While new and emerging capabilities might catch the eye, features that address data platform security, performance and availability remain some of the most significant deal-breakers when enterprises are considering potential data platform providers. This is especially true for mission-critical workloads. Adaptability, manageability, reliability and usability are also typically areas in which mature, incumbent software providers tend to have an advantage over emerging rivals. Although well-established as a developer data platform provider, MongoDB continues to add product experience functionality to compete with more established rivals. The launch of MongoDB 8.0 highlighted the recent advances the company has made in terms of performance, security, availability and resilience.

MongoDB was founded in 2007 and has established itself as one of the most prominent NoSQL database providers with its document-oriented database and associated cloud services. The MongoDB Atlas managed service is available on Amazon Web Services, Google Cloud and Microsoft Azure. While the company continues to make its software available for self-managed deployment on premises or in the cloud via MongoDB Enterprise Advanced and the MongoDB Community Edition free download, the proportion of MongoDB’s revenue associated with Atlas has been steadily increasing since it was launched in 2016 and accounted for 71% of MongoDB’s $478.1 million revenue in the second quarter of fiscal 2025. ISG’s Market Lens Cloud Study illustrates the extent to which the database market is now dominated by cloud, with 58% of participants deploying more than one-half of database and data platform workloads on cloud. MongoDB has benefited from a focus on the needs of development teams to deliver innovation through the development of data-driven applications. It continues to position its document database product as a developer data platform which is primarily used to support the development and deployment of net-new applications rather than as a direct replacement for relational databases. MongoDB is nevertheless keen to position MongoDB Atlas as a replacement for more traditional databases as part of application modernization strategies and has invested in a variety of capabilities to assist potential customers to refactor applications developed for relational databases.

The recent launch of MongoDB 8.0 is a reminder that while new developer-centric features might be key to developer-led adoption, enhancements related to adaptability, manageability and reliability are of critical importance to enterprise use cases. The latest version of the core database that underpins MongoDB Atlas, MongoDB Enterprise Advanced and MongoDB Community Edition features enhancements aimed at improving security, performance and availability. These include architectural optimizations to reduce memory usage and query times with more efficient batch processing to deliver better throughput, faster bulk writes and accelerated concurrent writes during data replication. MongoDB 8.0 also extends MongoDB’s Queryable Encryption capability, which was introduced in 2023. Designed to enable querying of sensitive data without the need to decrypt it, MongoDB Queryable Encryption now supports range queries. The latest version also adds data sharding improvements to accelerate horizontal scaling, as well as new controls that enable administrators to optimize database performance during spikes in demand.

MongoDB 8.0 also delivers enhanced developer-centric features focused on the development of AI applications. The company added support for vector search in 2023, which can help organizations improve trust in the output of GenAI by providing access to factually accurate and up-to-date information. I assert that through 2026, almost all enterprises developing applications based on GenAI will explore vector search and retrieval-augmented generation (RAG) to complement foundation models with proprietary data and content. MongoDB 8.0 adds support for vector quantization, which takes advantage of compression to reduce memory requirements for vector processing, leading to lower costs and improved performance. Earlier in 2024, the company also announced the launch of the MongoDB AI Applications Program (MAAP), which is designed to assist customers in developing and deploying applications enriched with GenAI. MAAP combines strategic advisory and professional services with MongoDB Atlas and services from partners including Anthropic, Amazon Web Services, Cohere, Google Cloud, LangChain and Microsoft Azure. Improved support for the modernization of existing applications was also delivered in early 2024 as the company added functionality to its MongoDB Relational Migrator tool that enables GenAI-powered conversion of SQL queries, triggers and stored procedures to the MongoDB Query API syntax.

While MongoDB continues to add new capabilities to its data platform, existing and potential customers should also be aware that the company recently announced plans to deprecate several previously heralded features. These include the Atlas Data Lake managed storage offering for analytics and the various components (Atlas Edge Server, Atlas Device Sync and Atlas Device SDK) that were designed to enable local data processing on mobile and IoT devices as well as in remote data centers or disconnected infrastructure. This will have come as a surprise to many, but the recent announcements highlight that the decision was a matter of development prioritization, rather than anything more significant. Unless directly impacted, I recommend that all enterprises evaluating potential data platform providers for new development and transformation projects should include MongoDB Atlas in their evaluations.

Regards,

Matt Aslett