Compaction in the Druid database has been evolving into use cases beyond improving query performance and reducing storage. This talk will first go over what is compaction, current use cases for compaction, a beginner’s guide on setting up compaction (and automatic compaction), and common pitfalls when setting up auto-compaction. The talk will then drive into short and long term plans for compaction in Druid. Future features include creating derived datasources / materialized views and automatically changing or maintaining different schemas for the same datasource based on the age of data.
Strategies for Managing Your Splunk Spend at Scale in 2026
Learn how a decoupled architecture for Splunk—powered by Imply Lumi and Federated Search—helps you keep more data searchable, reduce costs, and scale efficiently without changing existing Splunk workflows.
Watch nowObservability at a Breaking Point: How Decoupling Unlocks Speed, Scale, & Savings
Learn how decoupled observability helps you do more with your Splunk data, reduce costs, and scale efficiently with Federated Search.
Watch nowKeynote: Powering Event-Driven Data with Apache Druid
The distinction between OLTP and OLAP is becoming less relevant as data architectures shift toward entities and events. In this session, we’ll delve into how Apache Druid’s event-first approach synthesizes...
Watch now