Apache Druid was invented to address the lack of a data store optimized for
real-time analytics. Druid combines the best of real-time streaming analytics and
multidimensional OLAP with the scale-out storage and computing principles of
Hadoop to deliver ad hoc, search and time-based analytics against live data with
sub-second end-to-end response times. Today, thousands of companies worldwide
rely on Druid to provide real-time monitoring and analytics, including data-driven
companies like Netflix, Lyft, Pinterest and Alibaba. The largest Druid deployments
deliver sub-second analytics against millions of events per second and 100s of
petabytes of data.
This whitepaper provides an introduction to Apache Druid, including its evolution,
core architecture and features, and common use cases. Founded by the authors of the Apache Druid database, Imply provides a cloud-native solution that delivers real-time ingestion, interactive ad-hoc queries, and intuitive visualizations for many types of event-driven and streaming data flows.
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