Apache® Druid
Druid is a high performance, real-time analytics database that delivers sub-second queries on streaming and batch data at scale and under load.
Druid is a high performance, real-time analytics database that delivers sub-second queries on streaming and batch data at scale and under load.
Execute OLAP queries in milliseconds on high-cardinality and high-dimensional data sets with billions to trillions of rows without pre-defining or caching queries in advance.
Build real-time analytics applications that supports 100s to 100,000s queries per second at consistent performance with a highly efficient architecture that uses less infrastructure than other databases.
Unlock streaming data potential through Druid's native integration with Apache Kafka and Amazon Kinesis as it supports query-on-arrival at millions of events per second, low latency ingestion, and guaranteed consistency.
Druid utilizes scatter/gather for high speed queries with data preloaded into memory or local storage to avoid data movement and network latency
Configurable tiering with quality of service enables the ideal price-performance for mixed workloads, guarantees priority, and avoids resource contention
Ingested data is automatically columnarized, time indexed, dictionary encoded, bitmap indexed, and type-aware compressed
Loosely coupled components for ingestion, queries and orchestration combined with a deep storage layer enable easy & quick scale-up & scale-out
A connector-free integration with streaming platforms enables query-on-arrival, high scalability, low latency, and guaranteed consistency
Automatic data services including continuous backup, automated recovery, and multi-node replication ensure high availability and durability
Druid is proven in production at the world's leading companies at massive scale.
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Primary and secondary partitioning
Sergio Ferragut
Jan 27 2023
Using Apache Druid for analyzing streaming data
Julia Brouillette
Jan 27 2023
Why Confluent analyzes Kafka streams with Druid
Matt Armstrong
Dec 15 2022
Support for nested JSON columns in Druid
Karthik Kasibhatla
Dec 14 2022
Apache Druid's fit in the modern data stack
David Wang
Dec 2 2022