
A Practical Guide to Building GenAI Apps on a PostgreSQL-Compatible Database
As AI continues to advance, databases will need to integrate more sophisticated vector indexing techniques and support for emerging AI frameworks.
A Practical Guide to Building GenAI Apps on a PostgreSQL-Compatible Database reveals:
- How YugabyteDB’s powerful vector indexing capabilities support vector search through the pgvector extension
- The unique distributed architecture of YugabyteDB
- How YugabyteDB’s distributed design enhances scalability and performance for AI workloads
Download today to discover basic AI concepts, architectural considerations, as well as access to hands-on tutorials that demonstrate how to build your first GenAI application on various platforms
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Additional Resources

Deploy AI at Scale With YugabyteDB’s First Agentic AI Application and Extensible Vector Search
YugabyteDB is applying AI-first observability to deliver an agentic architecture. This means that intelligent agents not only analyze, but eventually automate and orchestrate performance tuning and optimization tasks.
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Intelligent Database Insights With Agentic AI for YugabyteDB Metadata
By bridging the gap between technical and non-technical users, this AI-powered approach enhances database efficiency, reduces operational overhead, and ensures that YugabyteDB runs at peak performance to deliver scalability and resilience without complexity.
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Doubling Down on PostgreSQL Compatibility: YugabyteDB Levels Up with PG15 Features
Our database experts have worked hard to make YugabyteDB the most PostgreSQL-compatible distributed database on the market. We are excited to build on our commitment to PostgreSQL by announcing that YugabyteDB now supports PG15 as a tech preview.
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