Industry Leaders Discuss the Integration of Databases, Big Data, and AI in Modern Enterprise Data Platforms

After a brief introduction to the rise of large language models (LLMs) and the AI for all trend, InfoQ and Yunqi Technology hosted a special live session with former Alibaba vice‑president Jia Yangqing, Yunqi co‑founder & CTO Guan Tao, and OtterTune co‑founder Zhang Bohan to discuss the evolving relationship between databases, big data, and AI.

Key discussion points:

Databases, big data, and AI are advancing together; modern startups first recruit data‑processing engineers, highlighting a renewed focus on data.

The concepts of “AI for Data” (using AI to improve data platforms) and “Data for AI” (using massive heterogeneous data to train AI) were contrasted, with examples such as embedding vectors and vector databases.

Enterprise data platforms should treat AI as a first‑class citizen, moving beyond traditional data warehouses, and must be open, extensible, and support plug‑in AI compute capabilities.

While data platforms and model platforms are complementary, neither can fully replace the other; a hybrid approach is required.

Practical criteria for evaluating data platforms include handling heterogeneous data, supporting multiple compute models, and being usable by non‑technical users.

Recommendations for building future‑ready platforms: adopt lake‑house architecture, ensure multi‑cloud flexibility, and prioritize simplicity and scalability.

The speakers emphasized that AI integration is still nascent, and enterprises should choose platforms that are easy to adopt, cost‑effective, and capable of scaling with AI workloads. They also noted that many enterprises lack dedicated data scientists, making user‑friendly AI‑enabled platforms essential.

At the end of the session, Guan Tao gave a brief product announcement for Yunqi Technology’s upcoming “Single Engine·All Data” platform, highlighting its multi‑cloud, fully managed, and AI‑ready design.