Vector data in Postgres: Size, TOAST, Filters and Performance
Wednesday, October 22 at 13:45–14:35
Room: Omega 2
Level: Intermediate
AI applications are changing how we use databases, and vector data is at the center of this change. By enabling semantic search within domain datasets, vectors allow for more intelligent and nuanced queries. But managing this data effectively requires understanding the challenges of vector size and its impact on storage and performance. This presentation explores practical strategies for storing, indexing, and querying vector data in operational databases and different factors impacting performance and management. Learn how to optimize your database for AI-powered applications and unlock the full potential of vector search.
