MongoDB
MongoDB empowers innovators to create, transform, and disrupt industries by unleashing the power of software and data. Its intelligent, unified data platform supports operational data, search, real-time analytics, and AI-powered retrieval for modern, real-time, hybrid, multi-cloud applications.
At a Glance
- Developers and developer-led teams
- Startups and AI-native companies
- Large enterprises
- Financial services
- +8 more
AI Tools by MongoDB
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MongoDB
Document Database for AI Agents
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Latest News
Launched Atlas Agent Engine to put AI agents into production without a new stack.
Launched MongoDB 9.0 (generally available) and Atlas Infinite (public preview) for AI-scale demand.
Announced CEO transition: CJ Desai stepped down and Dev Ittycheria became interim President and CEO.
Reported Q2 FY2027 revenue of $771.8 million, up 30% year over year, and raised full-year guidance.
Products & Services
Fully managed, multi-cloud database and intelligent data platform running across AWS, Azure, and Google Cloud.
Free, source-available MongoDB deployment for local development and self-managed workloads.
Self-managed commercial MongoDB for on-premises, private-cloud, and hybrid deployments with enterprise security, governance, and operations.
Integrated full-text, semantic, and vector retrieval capabilities using operational data without a separate search database.
Market Position
MongoDB positions itself as a developer-centric, intelligent document database and unified data platform spanning operational workloads, search, vector retrieval, streaming, analytics, and AI agents across any cloud or on premises. It competes with relational and cloud databases such as Amazon DynamoDB, Google Cloud Firestore/Spanner, Microsoft Azure Cosmos DB, Oracle, PostgreSQL, and with document/search platforms such as Couchbase, DataStax, Elasticsearch, and Redis. Its differentiation is the flexible document model, single Query API, multi-cloud Atlas, broad ecosystem, and integrated AI retrieval capabilities.
Leadership
Founders
Dwight Merriman
Co-founder of DoubleClick, where he served as CTO for ten years; also co-founder of Business Insider and Gilt Groupe.
Eliot Horowitz
DoubleClick veteran and co-founder of MongoDB/10gen; helped develop the flexible document database and served as MongoDB's CTO.
Kevin Ryan
Experienced entrepreneur and former DoubleClick executive; co-founded 10gen/MongoDB.
Executive Team
Dev Ittycheria
Interim President & CEO
Former MongoDB President and CEO for more than 11 years; co-founded BladeLogic, took it public, and later served as BMC president; partner and senior advisor at Sequoia.
Mike Berry
Chief Financial Officer
Former CFO at NetApp, McAfee, FireEye, Informatica, IO/Iron Mountain, SolarWinds, and i2 Technologies; board member at Calix and HubSpot.
Board of Directors
Founding Story
The founders experienced the limits of relational databases while DoubleClick was scaling beyond 400,000 ads per second. They believed a more flexible, scalable document model and an open development approach could help developers manage high-volume data and build applications without legacy database constraints. They formed 10gen in 2007 and launched MongoDB in 2009; the company adopted the MongoDB name in 2013.
Business Model
Revenue Model
Primarily subscription revenue from consumption-based, fully managed MongoDB Atlas and licenses/subscriptions for Enterprise Advanced, supplemented by professional services. FY2026 revenue was approximately 96% subscription ($2.37B of $2.46B) and $86.7M services.
Pricing Tiers
Free forever; 512 MB storage with shared RAM and vCPU.
For application development and testing; up to 5 GB storage.
Production workloads; 10 GB storage, 2 GB RAM, and 2 vCPUs in the displayed example.
Public preview on M10+ clusters for independently scalable compute and storage.
Target Markets
- Developers and developer-led teams
- Startups and AI-native companies
- Large enterprises
- Financial services
- Healthcare and life sciences
- Retail and ecommerce
- Modern application development
- AI-native applications and production AI agents
- Retrieval-augmented generation and semantic search
- Real-time operational workloads
- Event-driven and streaming applications
- Transactional applications
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