db on an agent, team, or workflow to persist its sessions and runs. Database implementations can also back memories, learnings, evaluations, knowledge content, traces, and schedules. Supported tables vary by provider.
- Chat history. Include previous messages in context for multi-turn conversations.
- Session persistence. Store session information and conversation history across requests.
- State management. Store session state across runs.
- Context control. Store session summaries and the runs used to build model context.
- Memory and knowledge. Store user memories, learned knowledge, and knowledge content metadata.
- Tracing and evaluation. Store detailed traces for debugging, monitoring, and building evaluation datasets.
- Data access. Query records in the database you configure and use them to build evaluation datasets or review run quality.
Quick Start

Guides
Chat History
Include previous messages in context for multi-turn conversations.
Session Storage
Store and retrieve session data from your database.
Session Summaries
Condense long conversations to manage token costs.
Storage Control
Choose what gets persisted to your database.
Works With Teams and Workflows
Agents, teams, and workflows all accept thedb parameter:
Supported Databases
Use SQLite for local development or choose a networked provider for a deployed application. See the database index.Async Support
For async applications, use the async database classes:Troubleshooting
MissingGreenlet exception
MissingGreenlet exception
You’re using a synchronous engine with an async database class. Use
create_async_engine from sqlalchemy.ext.asyncio.AsyncContextNotStarted exception
AsyncContextNotStarted exception
You’re using an async engine with a synchronous database class. Use
create_engine from sqlalchemy.