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Is MongoDB Rapidly Becoming the Go-To Database for AI Workloads?
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Key Takeaways
MongoDB is gaining from AI demand, aided by Voyage 3.5 and its fit for unstructured, fast-changing data.
The MCP Server preview enables AI agents to access data and tools, streamlining developer productivity.
MongoDB uses rerankers and embeddings to improve LLM accuracy and reduce hallucinations in AI outputs.
MongoDB (MDB - Free Report) has been steadily benefiting from the rising demand for AI-powered applications. In the first quarter of fiscal 2026, MongoDB reported revenues of $549 million, marking a 22% year-over-year increase. Atlas, its cloud platform, accounted for 72% of the total revenues, up 26% year over year. While enterprise adoption of AI is still in its early stages, MongoDB believes its integrated architecture will position it to capture long-term revenue growth as more developers build custom, high-value AI applications on its platform.
The company’s document model is well-suited for handling fast-changing, unstructured data required by real-world AI. The acquisition of Voyage AI strengthened this capability further, with Voyage 3.5 improving embedding accuracy and cutting storage costs significantly. Companies like LG Uplus are using their AI tools to support thousands of agents with faster, more accurate responses, reinforcing MongoDB’s position in the AI space.
MongoDB has added Anthropic’s Model Context Protocol (MCP) across all its databases, including Atlas, to simplify development and database tasks using AI. MCP lets AI agents like Claude, Cursor and GitHub Copilot access tools and data through a client-server model. With the MongoDB MCP Server now in public preview, developers can use natural language to query or explore data, streamlining workflows and boosting productivity.
MongoDB also aims to reduce AI hallucinations and increase accuracy through its advanced rerankers and domain-optimized embedding models. These tools rank LLM outputs based on contextual relevance, significantly improving reliability.
MDB’s Stiff Competition in the AI-Driven Database Market
MongoDB is seeing rising competition from Snowflake (SNOW - Free Report) and Elastic (ESTC - Free Report) , both of which are expanding their AI capabilities in the cloud database space.
Snowflake introduced native support for vector search and retrieval-augmented generation (RAG) workloads, and even after being acquired by MongoDB, Voyage AI’s models will still be available to Snowflake and to Voyage AI’s other users.
Elastic has expanded its AI capabilities with the Elasticsearch Relevance Engine, enabling native vector search, hybrid search and seamless integration with LLMs. With tools for contextual grounding and RAG workflows, Elastic helps developers build secure, production-ready AI applications using its data.
MDB’s Share Price Performance, Valuation and Estimates
MDB shares have lost 11.8% in the year-to-date (YTD) period, underperforming the Zacks Internet – Software industry’s growth of 15.8% and the Zacks Computer and Technology sector’s return of 7.7%.
MDB’s YTD Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, MongoDB stock is currently trading at a forward 12-month Price/Sales ratio of 7.03X compared with the industry’s 5.79X. MDB has a Value Score of F.
MDB Valuation
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for second-quarter fiscal 2026 earnings is pegged at 64 cents per share, which has remained unchanged over the past 30 days, indicating an 8.57% year-over-year decline.
Image: Bigstock
Is MongoDB Rapidly Becoming the Go-To Database for AI Workloads?
Key Takeaways
MongoDB (MDB - Free Report) has been steadily benefiting from the rising demand for AI-powered applications. In the first quarter of fiscal 2026, MongoDB reported revenues of $549 million, marking a 22% year-over-year increase. Atlas, its cloud platform, accounted for 72% of the total revenues, up 26% year over year. While enterprise adoption of AI is still in its early stages, MongoDB believes its integrated architecture will position it to capture long-term revenue growth as more developers build custom, high-value AI applications on its platform.
The company’s document model is well-suited for handling fast-changing, unstructured data required by real-world AI. The acquisition of Voyage AI strengthened this capability further, with Voyage 3.5 improving embedding accuracy and cutting storage costs significantly. Companies like LG Uplus are using their AI tools to support thousands of agents with faster, more accurate responses, reinforcing MongoDB’s position in the AI space.
MongoDB has added Anthropic’s Model Context Protocol (MCP) across all its databases, including Atlas, to simplify development and database tasks using AI. MCP lets AI agents like Claude, Cursor and GitHub Copilot access tools and data through a client-server model. With the MongoDB MCP Server now in public preview, developers can use natural language to query or explore data, streamlining workflows and boosting productivity.
MongoDB also aims to reduce AI hallucinations and increase accuracy through its advanced rerankers and domain-optimized embedding models. These tools rank LLM outputs based on contextual relevance, significantly improving reliability.
MDB’s Stiff Competition in the AI-Driven Database Market
MongoDB is seeing rising competition from Snowflake (SNOW - Free Report) and Elastic (ESTC - Free Report) , both of which are expanding their AI capabilities in the cloud database space.
Snowflake introduced native support for vector search and retrieval-augmented generation (RAG) workloads, and even after being acquired by MongoDB, Voyage AI’s models will still be available to Snowflake and to Voyage AI’s other users.
Elastic has expanded its AI capabilities with the Elasticsearch Relevance Engine, enabling native vector search, hybrid search and seamless integration with LLMs. With tools for contextual grounding and RAG workflows, Elastic helps developers build secure, production-ready AI applications using its data.
MDB’s Share Price Performance, Valuation and Estimates
MDB shares have lost 11.8% in the year-to-date (YTD) period, underperforming the Zacks Internet – Software industry’s growth of 15.8% and the Zacks Computer and Technology sector’s return of 7.7%.
MDB’s YTD Price Performance
Image Source: Zacks Investment Research
From a valuation standpoint, MongoDB stock is currently trading at a forward 12-month Price/Sales ratio of 7.03X compared with the industry’s 5.79X. MDB has a Value Score of F.
MDB Valuation
Image Source: Zacks Investment Research
The Zacks Consensus Estimate for second-quarter fiscal 2026 earnings is pegged at 64 cents per share, which has remained unchanged over the past 30 days, indicating an 8.57% year-over-year decline.
MongoDB, Inc. Price and Consensus
MongoDB, Inc. price-consensus-chart | MongoDB, Inc. Quote
MongoDB currently carries a Zacks Rank #2 (Buy). You can see the complete list of today’s Zacks #1 Rank (Strong Buy) stocks here.