Issue sub-second ad-hoc queries to group, filter, and aggregate data. Druid is ideal for powering multi-tenant user-facing applications.
Explore events immediately after they occur. Ingest data in streams or batches to unify real-time and historical views.
Existing Druid clusters have scaled to petabytes of data and trillions of events, ingesting millions of events every second. Druid is extremely cost effective, even at scale.
Druid runs on commodity hardware. Deploy it in the cloud or on-premise. Integrate with existing big data systems such as Hadoop, Spark, Kafka, Storm, Flink, and Samza.
Druid is a community led project. Join the fast growing community and work with developers from across the world.
Learn more about how many different organizations use Druid in production.
Try the quickstart and get started in minutes. Load your own data and query it.
Learn more about the high level architecture and concepts behind Druid.