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DirectoryData & AnalyticsStreaming & Real-Time AnalyticsDruid (Apache)

Druid (Apache)

Open Source

About Druid (Apache)

Apache Druid is a real-time analytics database. It executes OLAP queries on high-cardinality and high-dimensional data sets with billions to trillions of rows. It supports real-time analytics applications handling large numbers of queries per second. It integrates natively with Apache Kafka and Amazon Kinesis for streaming data. Developers and analysts can use SQL for data operations.

Used for

  • Executing OLAP queries on high-cardinality, high-dimensional datasets
  • Building real-time analytics applications
  • Ingesting streaming data from Apache Kafka and Amazon Kinesis
  • Performing join operations during data ingestion and at query-time
  • Querying and transforming data using SQL

Who it is for

  • Developers
  • Analysts

From Druid (Apache)'s own website, read 2026-10-23. How we build listings.

How to evaluate Streaming & Real-Time Analytics

This is how the CIOPages Research Team evaluates this category. It is not an assessment of Druid (Apache). It comes from our Streaming Data & Event Processing buyer guide.

25%
Throughput, Latency & Durability
Sustained throughput and tail latency at your partition count, ordering and exactly-once / at-least-once delivery guarantees, replication and multi-AZ durability, retention limits, and behavior under broker failure and rebalancing
20%
Operating Model & Architecture
Self-managed vs. fully managed vs. serverless vs. bring-your-own-cloud, KRaft (post-ZooKeeper) operations, diskless / object-storage-backed options, autoscaling, partition rebalancing, and upgrade and patching burden on your team
20%
Kafka-API Compatibility & Portability
Fidelity of the Kafka protocol (consumer groups, transactions, compaction), reuse of existing clients, connectors and tooling, lock-in to a single cloud, and the realistic effort to migrate in or out
15%
Stream Processing & Ecosystem
Native or integrated processing (Flink, Kafka Streams, Spark Structured Streaming, ksqlDB), connector catalog (CDC, sinks, sources), schema registry and governance, and direct landing into Iceberg / Delta lakehouse tables
10%
Security, Governance & Compliance
Encryption in transit and at rest, mTLS / SASL / OAuth and RBAC, audit logging, private networking, data residency and BYOC data-boundary control, and SOC 2 / ISO 27001 / GDPR coverage
10%
Cost Model & Economics at Scale
Pricing unit (capacity / throughput / consumption), inter-AZ and egress charges, storage and retention cost, processing billed separately, and how the bill behaves as volume, partitions, and connectors grow

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Quick Facts

druid.apache.org
CategoryData & Analytics
SubcategoryStreaming & Real-Time Analytics

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