Small is Beautiful - Using ClickHouse Data Warehouse for Edge Analytics

Explore the power of ClickHouse data warehouse for edge analytics in this 31-minute Linux Foundation talk. Delve into the key features of ClickHouse, including its Merge Tree table engine, data layout, and parallelized execution capabilities. Learn about installation platforms, compression techniques, and scaling options using shards and replicas. Discover how to leverage Kubernetes for flexible deployment and integrate edge and cloud environments. Gain insights into setting up a data warehouse and transforming an analytic server into a full-fledged analytic application.

Intro
What do analytic databases do?
Key features of ClickHouse
ClickHouse builds and installation Platforms
Merge Tree is the workhorse table engine
Merge Tree data layout
Adding CPUs boosts parallelized execution
Effect of codecs + ZSTD compression
From analytic server to analytic application
Kubernetes offers a flexible platform
ClickHouse scaling: shards and replicas Replicas concurrency
Operators encapsulate deployment logic
Setting up a data warehouse--the basics
Integrating edge and cloud environments