Druid

What Druid does

Apache Druid is an open-source, high-performance real-time analytics database project stewarded by the Apache Software Foundation, originally developed at Meta and contributed to the ASF. The project delivers sub-second OLAP query performance on streaming and batch data at scale, handling billions to trillions of rows and 100s to 100,000s of concurrent queries without pre-computation or caching. Its architecture combines loosely coupled ingestion, query, and orchestration components on top of a deep storage layer, with an optimized data format that automatically columnarizes, time-indexes, dictionary-encodes, bitmap-indexes, and compresses ingested data. Druid natively integrates with Apache Kafka and Amazon Kinesis for connector-free streaming ingestion at millions of events per second, and exposes a SQL API for end-to-end ingestion, transformation, and querying workflows. Schema auto-discovery and configurable tiering with quality-of-service prioritize mixed workloads while avoiding resource contention.

The project is released under the Apache License 2.0 and generates no direct revenue; commercial support, managed services, and cloud-hosted deployments are provided by third-party vendors and cloud providers. Distribution is community-led and self-serve: direct downloads from druid.apache.org, the GitHub repository, Slack community channels, Meetup groups, and the Tales at Scale podcast. Active development continues through a regular release cadence, with versions 35.0.1 (December 2025), 36.0.0 (February 2026), and 37.0.0 (May 2026) shipped within six months. Named enterprise adopters include Kong for API observability and insights, and Moso Networks for private 5G enterprise deployments in partnership with Qualcomm. The project occupies the streaming analytics / real-time OLAP category alongside major technology vendors including Microsoft, IBM, Oracle, SAP, Amazon, Google, TIBCO, Cloudera, and StreamSets.

Name

Druid

Legal name

Apache Druid

Website

https://druid.io

Company type

Private

Operating status

Operating

Short description

Apache Druid is an open-source, real-time analytics database under the Apache Software Foundation that delivers sub-second OLAP queries on streaming and batch data at billions-to-trillions-of-rows scale, serving enterprise analytics and streaming-data use cases via native Kafka and Kinesis integrations.

Ownership category

akta.pro rank

Headquarters

HQ city

San Francisco

HQ country

United States

HQ region

North America

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Infrastructure, Operations, Marketing or Sales, Others

Revenue model

1. Open Source Distribution: Apache Druid is distributed as open-source software under the Apache License 2.0. The project is maintained by the Apache Software Foundation with contributions from the community. Commercial support, managed services, and cloud deployments may be offered by third-party vendors.

Go-to-market motion1 record

Distribution channels3 records

Marketing channels7 records

Core offering

Apache Druid is a high-performance, real-time analytics database that executes sub-second OLAP queries on streaming and batch data at massive scale. The software is built on a loosely coupled architecture that separates ingestion, queries, and orchestration components and combines them with a deep storage layer for elastic scaling. It is released under the Apache License 2.0 as an open-source project of the Apache Software Foundation and is downloaded and self-deployed by enterprise users.

Product overview

Apache Druid is a single unified real-time analytics database platform. Druid provides sub-second OLAP query performance on streaming and batch data at scale through a loosely coupled architecture combining ingestion, queries, and orchestration components with deep storage. The platform natively integrates with Apache Kafka and Amazon Kinesis for true stream ingestion, and offers SQL support for end-to-end data operations. Key capabilities include an Interactive Query Engine using scatter/gather for high-speed queries, tiering with quality-of-service for mixed workloads, automatic data columnarization with compression, automatic schema discovery, and flexible joins support during both ingestion and query-time execution. Druid is released under the Apache License 2.0 with recent versions including 37.0.0 (May 2026), 36.0.0 (Feb 2026), and 35.0.1 (Dec 2025).

Differentiator

Problem solved

Functional benefit

Products and services

• Apache Druid A high-performance, real-time analytics database that delivers sub-second OLAP queries on streaming and batch data at scale. Designed for engineering and analytics teams at enterprises that need to query high-cardinality, high-dimensional data sets with billions to trillions of rows and to support high concurrency, with native integrations for Apache Kafka and Amazon Kinesis streaming ingestion. Released under the Apache License 2.0.

Quantifiable outcome

• Sub-second OLAP queries on billions to trillions of rows without pre-caching
• +3 more outcomes

Named customers2 records

Segments2 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration2 records

AI capability1 record

Feature9 records

Partnerships

Two partnerships are on record, tiered core and minor.

• Moso NetworkscoreTechnology or Integration · 5 March 2026Moso Networks partners with Druid for pre-integrated software solutions that simplify private 5G systems for enterprises. Druid is used alongside Qualcomm SoC-based radios and Moso's Intelligent Management Platform to reduce technical complexity in enterprise private 5G deployments, supporting edge AI applications requiring low latency and high throughput.
• Market ecosystem with Microsoft, IBM, Oracle, SAP, Amazon, Google, TIBCO Software, Cloudera, StreamSetsminorOthers · 24 April 2024Druid is identified as a key company in the Streaming Analytics Market alongside major technology providers including Microsoft, IBM, Oracle, SAP, Amazon, Google, TIBCO Software, Cloudera, and StreamSets. This positioning reflects Druid's presence in the competitive streaming analytics landscape.

Scale indicators3 records

Recent moves5 records

Expansion highlights4 records

Emerging players

• Materialize: Materialize provides a streaming SQL database built on incremental view maintenance, overlapping with Druid on the real-time, sub-second analytics use case but with a different (incremental compute) architecture.
• TimescaleDB: TimescaleDB is a time-series database built on PostgreSQL that competes with Druid for high-cardinality time-series and event analytics workloads, especially in observability and IoT scenarios.

Broad incumbents

• Snowflake: Snowflake is the leading cloud data warehouse and data platform and competes with Druid for analytical workloads, particularly as it expands into streaming and near-real-time analytics.
• Elasticsearch: Elasticsearch is a broadly adopted analytics and search engine with real-time indexing capabilities, making it a wider incumbent alternative for organizations considering Druid for analytical or observability workloads.
• Databricks: Databricks offers a unified data and AI platform (including Delta Lake and Photon-powered SQL) that competes with Druid for large-scale analytical workloads and increasingly for streaming/real-time use cases.

Direct peers

• ClickHouse: ClickHouse is an open-source columnar OLAP database engineered for sub-second analytical queries on very large datasets, sharing Druid's core value proposition of fast OLAP at scale while serving similar enterprise analytics workloads.
• Imply.io: Imply.io is the leading commercial vendor offering a managed product and cloud service built directly on Apache Druid, making it the primary commercial ecosystem peer that monetizes the Druid user base.
• StarRocks: StarRocks (formerly Apache Doris) is a high-performance MPP analytical database optimized for real-time, sub-second multi-dimensional analytics on large datasets, directly comparable to Druid's real-time OLAP workload.
• Apache Flink: Apache Flink is a stream-processing framework widely used for real-time event pipelines that frequently sit alongside or integrate with Druid; both target sub-second latency on streaming workloads and overlap in real-time analytics stacks.
• Apache Pinot: Apache Pinot is an Apache-incubating real-time distributed OLAP data store designed for low-latency analytics on streaming data, making it the closest functional peer to Druid within the open-source OLAP/streaming analytics category.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat4 records

Key risks6 records

Key highlights6 records

Customer concentration

• GitHubgithub.com/apache/druid
• YouTubemusic.youtube.com/playlist?list=PLDZysOZKycN4ndlSxImrdFugdQ2NYbYMv

Revenue estimate

Valuation estimate

Number of profiles

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Druid