A practical engineering reference for running Apache Druid at scale. Manage segment
lifecycles, automate ingestion specs, tune compaction, and orchestrate resilient
Python pipelines — without guesswork.
Built for OLAP data engineers, analytics platform developers, Python pipeline builders,
and DevOps teams, this site distills production patterns for the full segment journey:
creation, compaction, pruning, and expiration. Each guide pairs operational theory with
copy-ready code so you can move from concept to deployment quickly.
Explore deep dives on segment architecture and the columnar storage engine, end-to-end
ingestion orchestration with validation and async execution, storage optimization through
compaction scheduling and retention sync, and the replication, tier placement, and balancing
that keep segments highly available under node loss.
New to the site? These four guides open one doorway into each topic area — start with the
fundamentals, then jump straight to the problem you're solving today.
Four focused topics cover the Druid segment lifecycle end to end — from architecture
fundamentals, through ingestion orchestration and compaction, to the replication and balancing
that keep segments available. Start with the fundamentals, then drill into the topic you need.