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Abstract:

This webinar provides a technical overview of the vector indexing capabilities to be introduced in IBM Db2 v12.1.5, building on the native vector data type available since v12.1.2. We examine how Db2 implements approximate nearest neighbor (ANN) search using a DiskANN-based index to efficiently query high-dimensional embeddings, and how these indexes integrate with the optimizer to combine similarity search with relational predicates in a single execution plan. The session also covers key performance considerations—such as graph build parameters, search parameters, and I/O behavior—along with benchmark insights and practical tuning strategies to balance recall, latency, and resource utilization.

Speaker(s): 

Christian Garcia-Arellano

Christian Garcia-Arellano is STSM and Db2 OLTP Architect at the IBM Toronto Lab, and has a MSc in Computer Science from the University of Toronto. Christian has been working in various DB2 Kernel development areas since 2001. Initially Christian worked on the development of the self tuning memory manager (STMM) and led various of the high availability features for DB2 pureScale that make it the industry leading database in availability. More recently, Christian was one of the architects for Db2 Event Store, and the leading architect of the Native Cloud Object Storage feature in Db2 Warehouse. Christian can be reached at cmgarcia@ca.ibm.com.

Zach Hoggard

Zach Hoggard is a Senior Software Developer for IBM Db2 in the IBM Data & AI organization at the IBM Canada Lab. Zach has over 10 years of Db2 Kernel development experience and his areas of expertise are the Buffer Pool and Storage Manager components of Db2, but also has extensive experience with all Db2 Kernel components. Zach has strong interest in Db2 problem determination as well as Db2 system design in the Kernel area. Zach is an IBM Certified Database Associate for Db2 v11.1 and v10.5, and holds a Bachelor’s degree in Software Engineering from Western University in London, Ontario, Canada.

Chris Stojanovski

Chris Stojanovski is an Advisory Software Developer for IBM Db2 in the IBM Data & AI organization at the IBM Canada Lab. Chris has been with IBM for five years, contributing primarily to the Index Manager team while also working with Data Management Services and XML. As a member of the Db2 Kernel team, he is passionate about expanding his knowledge of database internals and system architecture. Chris holds a Bachelor of Computer Science from the University of Waterloo, a Bachelor of Business from Wilfrid Laurier University, and a Master’s in Computer Science from Western University.