MongoDB has grown its customer base to 57,100 customers, with total new customer additions the highest in over six years, the data platform provider said on a fiscal Q1 2026 earnings call late Wednesday.
That includes the addition of ~8,000 new customers using its Atlas cloud database-as-a-service since the same quarter last year, it said; a shift that comes as MongoDB also looks to drive more upmarket enterprise deals.
(“We've signed some very, very large deals with some very, very large enterprises” said CEO Dev Ittycheria of the GTM shift, adding on the call that “our self-serve business is starting to acquire mid-market logos, serving them more efficiently without ceding ground to anyone else…”)
MongoDB, which provides a “document model” database, its Atlas DBaaS and host of associated native capabilities like search, queryable encryption and now AI models, raised its full-year guidance to $2.29 billion. As well as targeting new “traditional” applications and application modernisation moves, it is looking to capture homegrown AI application workloads.
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“MongoDB now brings together three things that modern AI-powered applications need: Real-time data, powerful search and smart retrieval” said CEO Dev Ittycheria, speaking two weeks after the company’s recent acquisition Voyage AI released its latest embedding model, Voyage 3.5. (Voyage specialises in context-aware retrievals from unstructured data, for example to reduce hallucination/improve accuracy in RAG workflows.)
He added in an analysts Q&A: “Anyone can use an ISV to run their business, but that doesn't give them a competitive advantage because their competitors could use the same ISV. What really gives them a competitive advantage is building custom solutions using AI to transform their business.
"When people start really learning about MongoDB, the document model can handle these complex data structures. We have best-in-class Voyage embeddings to improve the accuracy of these results to help people get comfortable with using AI. And by integrating text search, vector search and embeddings and operational data, that's a unique differentiator. It makes the developer's life easy, reduces cost and complexity. So we feel we're well positioned for this… most enterprises are still early in the adoption of AI.”
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