Turbopuffer
Serverless vector search on object storage
About Turbopuffer
Turbopuffer is a serverless vector database built on object storage, designed for cost-efficient and scalable vector search workloads. By leveraging object storage as its primary persistence layer, Turbopuffer separates compute and storage, enabling efficient scaling and reduced infrastructure costs. It provides fast similarity search and indexing capabilities suitable for AI applications such as semantic search, AI memory systems, and large-scale retrieval workloads. Turbopuffer is optimized for cloud-native environments and allows developers to deploy vector search infrastructure without managing servers or complex distributed systems.
Key features
Pricing
Common use cases
Common questions about Turbopuffer
Is Turbopuffer production-ready?
Yes, Turbopuffer is a fully managed cloud service designed for production workloads. It handles infrastructure, scaling, backups, and monitoring automatically.
How does Turbopuffer pricing work?
Turbopuffer offers 2 pricing tiers, typically based on storage, query volume, and performance requirements. Check their pricing page for current details.
What are the main use cases for Turbopuffer?
Turbopuffer is commonly used for cost-efficient vector search, large archival datasets, batch processing, and similar applications requiring semantic similarity search.
Does Turbopuffer integrate with popular AI tools?
Most vector databases integrate with LangChain, LlamaIndex, and popular embedding providers. Check the Turbopuffer documentation for specific integration guides and examples.
Not sure if Turbopuffer is right for you?
Compare it side-by-side with other vector databases to find the best fit for your project.