SINGAPORE, June 29, 2026 /PRNewswire/ -- OceanBase today announced the release of OceanBase AI Database, a comprehensive portfolio designed to enable enterprises to manage multimodal data, deliver real-time trusted data context to AI agents, and simplify fragmented data architectures.
Built around a unified LakeBase architecture, the OceanBase AI Database integrates the openness and scale of data lakes, the transaction processing and real-time serving capabilities of databases, and native multimodal data processing capabilities. This enables enterprises to manage structured, unstructured, and vector data within a single, strongly consistent data foundation.
OceanBase AI Database introduces a series of data products tailored 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, enabling enterprises to build a robust data foundation for the AI era.
- 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 modeling and agent collaboration, and turning data silos into callable data services.
- OceanBase DataPilot: Acting as a business intelligence agent for enterprises, DataPilot can generate analytical reports, data dashboards, and trusted answers through natural language, making data intelligence highly accessible to non-technical users.
Over the past years, large language models have evolved rapidly. However, the deployment of enterprise AI applications has hit a plateau. While AI models have largely solved the reasoning problem, the next challenge for enterprises now lies in whether AI can access, understand, and act on trusted business data.
As AI agents move from chat interfaces into production workflows, they require continuous access to memory, context, state, and enterprise data. At the same time, enterprise data is becoming increasingly multimodal, spanning business records, documents, images, audio, video, logs, and vectors. Traditional multi-system architectures struggle to provide the real-time, consistent, and governed context that AI agents require.
Meanwhile, although AI is fundamentally changing the paradigm of data management, and data forms, flows, and interactions are undergoing significant transformations, four fundamental baselines remain non-negotiable for enterprises: consistency, scalability, reliability, and real-time performance.
To address this, OceanBase proposes the LakeBase architecture, which brings the openness and massive storage capabilities of data lakes together with the consistency, online serving, and reliability of databases. By extending transaction consistency, high availability, and elasticity proven in financial core systems to data lake and multimodal data scenarios, OceanBase AI Database provides a unified data foundation for modern AI applications.
"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 data lake and database. It is about bringing multimodal data, real-time serving, transaction consistency, and open compute into a single architecture."
Compared to traditional solutions, the OceanBase AI Database can reduce the overall Total Cost of Ownership (TCO) by approximately 30% to 50%. This has already been validated in various AI application scenarios, including Ant Group's AQ (Ant A-Fu in Chinese) and Lingguang. Notably, leveraging Lingguang, users have cumulatively generated tens of millions of "flash apps", demonstrating OceanBase's ability to provide isolated, low-cost data environments at massive scale.
Over the past few years, OceanBase has already supported AI application deployment across multiple industries. Leading enterprises, including Lalamove, China Unicom, and Trip.com, have adopted OceanBase to build stable, high-performance RAG, hybrid search, and AI-powered data applications, empowering higher-quality search and question-answering experiences.
About OceanBase
OceanBase is a distributed database launched in 2010. It provides strong data consistency, high availability, high performance, cost efficiency, elastic scalability, and compatibility with mainstream relational databases. It handles transactional, analytical, and AI workloads through a unified data engine, enabling mission-critical applications and real-time analytics.
To learn more, please visit: https://www.oceanbase.com/
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OceanBase Unveils AI Database: A New Product Portfolio Unifying Multimodal Data, Real-Time Analytics, and AI Agent Workloads
