Real-time OLAP databases · Apache Software Foundation

Apache Druid

Open-source real-time analytics database that ingests streaming and batch data for interactive dashboards.

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Apache Druid is an open-source distributed database built specifically for fast slice-and-dice analytics on event-driven data, such as clickstream, application metrics and IoT telemetry. It separates ingestion, storage and query into distinct process types, uses columnar storage with pre-computed indexes (including bitmap indexes), and can absorb data from Kafka or Kinesis with sub-second latency while queries run against it concurrently. Druid supports both real-time streaming ingestion and batch loads from files or data lakes, and it exposes both a native JSON query API and a SQL interface. It is self-hosted by default, requiring an operator to manage ZooKeeper, deep storage and multiple node types, though managed offerings exist (see Imply). Druid is typically shortlisted for user-facing analytics products and operational dashboards that must stay responsive as new data streams in continuously.

At a glance

Vendor Apache Software Foundation
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Teams building user-facing or operational dashboards over continuously streaming event data.

Pricing

Free and open source under the Apache Software Foundation; commercial managed hosting is available separately through Imply.

Pricing has not been verified yet — see the vendor's site.

Features

  • Real-time streaming ingestion from Kafka/Kinesis
  • Columnar storage with bitmap indexing
  • Sub-second query response on high-cardinality data
  • Native JSON query language and Druid SQL
  • Automatic data rollup and retention rules
  • Multi-tenant query and ingestion isolation
  • Approximate algorithms for count-distinct and quantiles

Integrations

Profile last reviewed September 21, 2026

Head to head

Alternatives

Imply Managed and self-hosted Apache Druid platform built by Druid's original creators. Apache Pinot Open-source distributed OLAP database built by LinkedIn for low-latency analytics serving at high query volume. StarTree Fully managed cloud service for Apache Pinot, built by Pinot's original creators. ClickHouse Open-source columnar database built for sub-second aggregate queries over billions of rows.

Apache Druid in the index now

Terms to know

OLAP (online analytical processing) A category of technology optimized for fast, multi-dimensional aggregation and slicing of data for analysis. Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. Dashboard A visual display of the metrics a team needs to monitor, usually updated on a schedule or in real time. Columnar storage A file and database layout that stores each column's values together, instead of storing each row together. Real-time OLAP An analytical database that ingests streaming data continuously and answers aggregation queries with sub-second latency. Clickstream The raw, timestamped sequence of pages, clicks, and interactions a single visitor generates while browsing a site or app.

Related guides

How to choose a real-time OLAP database Real-time OLAP databases trade operational complexity for speed on fresh data — the decisions are architecture, query concurrency, and who runs it.