is a serverless, multi-tenant search engine that seamlessly integrates vector and full-text search on object storage. We quite like its architecture and , particularly its focus on durability, scalability and cost efficiency. By using object storage as a write-ahead log while keeping its query nodes stateless, it¡¯s well-suited for high-scale search workloads.
Designed for performance and accuracy, turbopuffer delivers out of the box, even for complex filter-based queries. It caches cold query results on NVMe SSDs and keeps frequently accessed namespaces in memory, enabling low-latency search across billions of documents. This makes it ideal for document retrieval, vector search and retrieval-augmented generation (RAG) AI applications. However, its reliance on object storage introduces trade-offs in query latency, making it most effective for workloads that benefit from stateless, distributed compute. turbopuffer powers high-scale production systems like Cursor but is currently only available by .
