Apache Druid is an analytics data store for event-driven data. In more technical terms, Druid is a real-time columnar timeseries database that scales effortlessly.

It has a web application component to visualize the data.

It is common to use Apache Kafka as a buffer and feed events form Kafka to Druid. Druid should be able to use any event-oriented or time series Kafka topics without much of a hassle.

Druid doesn't support joins so you must do that in pre-processing phase e.g. with Spark or Flink.

Common use-cases:

• Network flows
• User activity
• Device metrics
• Application performance
• Digital marketing advertisement data
• Business intelligence

Data is stored into segments. Segments are immutable, and you configure how they are created; hourly, daily, monthly.

Druid installation is quite heavy. You need a SQL database, Zookeeper, S3 and a bunch of servers. Kubernetes + Helm can help with the setup.

Sources

• Druid Website