Analytics over traditional row-oriented relational databases does not scale. For read-heavy workloads that require aggregating huge numbers of rows column-oriented databases deliver massive performance improvements. While row-oriented relational database technology has been remarkably stable since the 1970s, column storage is a relatively new invention with ongoing innovation and improvement through systems like ClickHouse, DuckDB, Vertica, BigQuery, Redshift and SAP HANA.

This presentation introduces the design ideas that make column stores so powerful, such as cache-friendly access patterns, vectorized execution and advanced compression schemes. We will demystify the internal machinery of column stores, including columnar storage layout, sophisticated encoding schemes, and column-oriented query execution.

You’ll leave this talk with a clear understanding of where column-stores shine, how they differ from relational databases, and why modern analytics platforms are built on these principles. Whether you’re a practitioner curious about database internals or just looking to understand the tech powering today’s big data systems, this presentation will give you an approachable, hands-on introduction to the world of column-oriented databases.