Qdrant vs MongoDB
Side-by-side comparison of AI visibility scores, market position, and capabilities
Open-source vector database written in Rust. $50M Series B (March 2026), $87.8M total. 250M+ downloads, 29K GitHub stars. Clients: Tripadvisor, HubSpot, Bosch. Private.
About
Qdrant is a vector search engine company founded in 2021 by Andre Zayarni, headquartered in Berlin, Germany. It develops a high-performance open-source vector database optimized for AI retrieval and similarity matching, written in Rust. In March 2026, Qdrant raised $50M Series B led by Advance Venture Partners, bringing total funding to ~$87.8M.
Document database leader with $1.7B revenue; Atlas Vector Search positions MongoDB as the core AI application data layer for RAG and semantic search; flexible BSON document model serves 47,000+ customers on AWS, Azure, and Google Cloud.
About
MongoDB is a leading document-oriented NoSQL database company providing a flexible, developer-friendly data platform for modern applications that require horizontal scalability, flexible schemas, and rich query capabilities. Founded in 2007 by former DoubleClick engineers and headquartered in New York City, MongoDB pioneered the document database model using JSON-like documents (BSON) rather than relational tables, enabling developers to store data in structures that naturally match application objects without complex ORM mappings. The company is listed on NASDAQ and generates approximately $1.7 billion in annual revenue.
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