qdrant

Qdrant addresses the need for a high-performance vector database and search engine, crucial for applications involving AI and machine learning. Backend/API teams, ML/AI teams, and engineering managers will find it particularly beneficial for building scalable solutions that require efficient similarity searches and embeddings management. With a maturity level indicating it is production-ready, Qdrant has gained 1,526 stars (5.6%) over 85 days, reflecting its healthy adoption in the open source community. However, it may not be the right choice for projects with minimal AI components or those requiring a simpler database solution.

This is a strong choice for projects that require advanced AI search capabilities and efficient handling of vector data. Teams should consider alternatives if their needs are more aligned with traditional databases or if they require simpler data structures.

Qdrant is ideal for backend/API teams and ML/AI teams working on applications that involve complex data retrieval and analysis. It is commonly integrated into products like recommendation systems, image search platforms, and any system that leverages machine learning for data processing.

Latest commit: 2026-02-03. Over the past 86 days, this repository gained 1.5k stars (+5.6% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.