# OceanBase Unveils AI Database: A New Product Portfolio Unifying Multimodal Data, Real-Time Analytics, and AI Agent Workloads

- Link: https://www.thailand-business-news.com/pr-news/oceanbase-unveils-ai-database-a-new-product-portfolio-unifying-multimodal-data-real-time-analytics-and-ai-agent-workloads
- Published: 2026-06-29T19:00:00+07:00
- Author: PR Newswire

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.

[⌊Charlie Yang, CTO of OceanBase, Unveils the OceanBase AI Database⌉⌊Charlie Yang,
CTO of OceanBase, Unveils the OceanBase AI Database⌉[
Charlie Yang, CTO of OceanBase,
Unveils the OceanBase AI Database

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/](https://www.oceanbase.com/)

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