Case Study: Bloop achieves fast, reliable semantic code search with Qdrant

Bloop powers semantic code search across 2.8 million lines with Qdrant

bloop is a fast code-search engine that helps developers navigate and understand large codebases. Their challenge was to build a semantic search engine capable of instantly finding relevant code by meaning, not just text, which becomes increasingly difficult as a codebase grows to millions of lines. They required a fast, reliable vector search database to serve as the core component of this engine.

Qdrant provided its vector search database as the solution, which bloop found to be the top contender in the field. By using Qdrant, bloop achieved excellent semantic search performance while using a reasonable amount of resources, enabling them to handle concurrent search requests and keep their application fast, accurate, and reliable even on large codebases like Rust's 2.8 million lines of code.

Bloop