turbopuffer
Serverless vector and full-text search engine built on object storage, with an HTTP API for namespaces and queries.
- Category
- Cloud & Data Platforms
- Type
- Vector database
- Interface
- REST API
- Built with
- Connect Any API
- Credentials
- Access token
02Data
What you can sync.
- Documents
- Namespaces
- Query results
Put turbopuffer documents next to revenue and usage, so every cost has an owner and a reason.
Need more? Name any other turbopuffer data the API returns, and the AI adds it to the connector.
03Credentials
Credentials you will need.
- An access token
turbopuffer uses an access token. You add the credentials once, when the AI asks for them, and it tells you where to create them in turbopuffer if you need help.
04How it works
How it works in DataMind.
-
Pick turbopuffer.
Open Lake, pick turbopuffer in the source picker and name the connection. Connect Any API opens with a ready prompt that points the AI at the turbopuffer API docs.
-
Answer a few questions.
The AI reads the turbopuffer documentation, then asks which credentials you will use, which data to sync (for example documents and namespaces), whether you want a one-time load or a recurring sync, and which accounts or filters apply.
-
Your data lands in Lake.
It builds the connector, tests it and shows you sample rows. Then turbopuffer data loads into your Lake on your schedule, ready for the Warehouse, DataPrism BI and AI Minds.
