SeekDB: An AI-Native State Store for Autonomous Agents

OceanBase introduces SeekDB, a specialized state store designed for AI agents, featuring MySQL compatibility, hybrid search capabilities, and Copy-On-Write (COW) sandboxing for efficient state management.

Architecting State Management for AI Agents

The evolution of autonomous AI agents requires a robust mechanism for maintaining state, memory, and context. SeekDB emerges as an AI-native state store specifically engineered to handle the unique demands of agentic workflows. By providing a reliable infrastructure for persisting agent states, SeekDB enables the development of more complex, long-running AI applications that require consistent memory across multiple sessions.

Core Technical Features

Hybrid Search Capabilities

To support the retrieval needs of Large Language Models (LLMs), SeekDB implements a hybrid search architecture. It integrates both vector search—essential for semantic retrieval and RAG (Retrieval-Augmented Generation) workflows—and traditional full-text search. This duality allows agents to perform precise keyword lookups alongside nuanced semantic queries, optimizing the accuracy of context retrieval.

Deployment Flexibility and Compatibility

SeekDB is designed for versatility in deployment, offering both embedded and server-based modes. This allows developers to integrate the state store directly into their application process for low-latency access or deploy it as a standalone server for centralized state management. Furthermore, its MySQL compatibility ensures that developers can leverage existing SQL ecosystems and tools, reducing the learning curve and integration friction.

Advanced State Versioning via COW Sandboxes

One of the most distinctive features of SeekDB is the implementation of Copy-On-Write (COW) sandboxes. By supporting FORK and MERGE operations, SeekDB allows agents to create isolated snapshots of their current state. This is particularly critical for "trial-and-error" reasoning paths, where an agent can explore a hypothetical trajectory in a sandbox and either merge the successful outcome back into the main state or discard the branch without affecting the primary data store.