OceanBase unveils AI Database, a portfolio designed to enable enterprises to manage multimodal data, deliver real-time trusted data context to AI agents, and simplify fragmented data architectures.
“As AI moves from answering questions to taking actions, databases must evolve from systems of record into trusted context engines for AI,” said Charlie Yang, chief technology Officer of OceanBase. “OceanBase AI Database is not about stitching together a data lake and a database. It is about bringing multimodal data, real-time serving, transaction consistency, and open compute into a single architecture.”
OceanBase AI Database
OceanBase AI Database offers a unified, strongly consistent foundation capable of managing structured, unstructured, and vector data seamlessly.
It includes a series of data products for the AI era:
- OceanBase Lakebase: Serving as the underlying data engine, Lakebase enables structured, unstructured, and vector data to be managed, processed, searched, and served within a unified architecture.
- OceanBase DataStudio: Built upon the Lakebase engine, DataStudio is a data production, governance, and services platform, covering the entire lifecycle from data ingestion, processing, and orchestration to semantic modelling and agent collaboration, and turning data silos into callable data services.
- OceanBase DataPilot acts as an intuitive business intelligence assistant, enabling enterprises to generate analytical reports, dashboards, and trusted answers through natural language, making data insights accessible to all users.
LakeBase architecture
To maintain enterprise-grade consistency, scalability, reliability, and real-time performance, OceanBase proposes the LakeBase architecture, which combines the openness and massive storage capabilities of data lakes with the consistency, online serving, and reliability of databases.
The portfolio claims to provide a unified data foundation for modern AI applications.
