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  • Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics ("OLAP" queries) on large data sets. Most often, Druid powers use cases where real-time ingestion, fast query performance, and high uptime are important.
    Druid is commonly used as the database backend for GUIs of analytical applications, or for highly-concurrent APIs that need fast aggregations.
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  • Unlock streaming data potential through Druid's native integration with Apache Kafka and Amazon Kinesis as it supports...
  • Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics ("OLAP" queries) on large data sets.
  • In this article we will have a complete overview of the Apache Druid framework, starting from what a timeseries is, how we could handle this kind of data, and a...
  • Druid excels at powering UIs, running operational (ad-hoc) queries, or handling high concurrency.
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  • Druid is a column-oriented, open-source, distributed data store written in Java. Druid is designed to quickly ingest massive quantities of event data...
  • This article gently presents the OLAP-like timeseries database Apache Druid, by outlining its architecture and the way that its components interact for data ingestion...
  • Apache Druid is extremely efficient on large time series datasets, enabling real-time analytics on use cases that were previously unmanageable.
  • Apache Druid also has a large list of enterprise-grade features, such as clustering and replication, including masterless clustering.
  • Druid includes built-in indexing services for Apache Kafka and Amazon Kinesis that enable event-based ingestion for real-time analytics.
  • Examples of such hybrid data warehouses include Apache Druid and Delta Lake.