Apache Druid
A high-performance real-time analytics database optimized for fast queries and data ingestion, supporting streaming and batch loads.
Smart Download
Visit Project Homepage
No installer available yet — head to the source repository
High-performance real-time analytics database designed for fast queries and flexible ingestion.
Core Features
- Sub-second query latency for real-time dashboards and ad-hoc analytics
- Native support for streaming (e.g., Kafka) and batch ingestion
- Built-in web console for cluster management, datasources, and queries
- HTTP and JDBC APIs with SQL compatibility
- Horizontal scalability and high concurrency
What It Can't Do
- •Not suitable for OLTP workloads – no ACID transactions or complex joins,Cluster deployment requires careful configuration (ZooKeeper, deep storage like HDFS/S3),Memory-intensive; plan hardware according to data size and query patterns
Use Cases
- Real-time monitoring dashboards
- User behavior and clickstream analytics
- IoT time-series data querying
- Embedded analytics within applications
Detailed Introduction
Apache Druid is a high-performance real-time analytics database designed for fast queries and data ingestion. It excels at powering user interfaces, running operational (ad-hoc) queries, and handling high concurrency. Druid supports both streaming and batch data ingestion, provides a built-in web console for management, and offers HTTP and JDBC APIs. It is commonly used for real-time dashboards, embedded analytics, and OLAP workloads. Compared to alternatives like ClickHouse or Snowflake, Druid offers a more native real-time streaming ingestion pipeline and a user-friendly web interface for cluster management, making it ideal for use cases where low-latency insights are critical.
Troubleshooting & FAQ (2)
TroubleshootingWhat causes the 'Function[like] pattern argument must be a literal' error when using LIKE with UPPER() in Apache Druid SQL?
This error occurs because Druid's SQL optimizer (based on Apache Calcite) requires the pattern argument of LIKE to be a string literal (constant) during query planning. When you apply functions like UPPER() directly to the pattern, the planner cannot reduce it to a literal at compile time, causing the error. A workaround is to pre-evaluate the function by using a Common Table Expression (CTE) or subquery, forcing the function result to be computed before the LIKE filter is applied. Example: WITH t AS (SELECT 'a string' AS col), t2 AS (SELECT col, UPPER(col) AS upper_col FROM t) SELECT * FROM t2 WHERE upper_col LIKE UPPER('a%'). Alternatively, ensure the pattern is a literal constant by moving the UPPER() call outside if possible. This is a known limitation in Druid versions up to at least 30.0.0, and may be addressed in future releases.
TroubleshootingWhy do Apache Druid tasks fail with 'Attempting to publish with empty segment set' error when using multiple replicas?
There is a known race condition in Druid (observed in v33.0.0) where redundant tasks with replicas > 1 conflict during segment publishing, causing this error. The only reliable workaround is to set the task replicas count to 1. This avoids the race but may cause ingestion downtime during worker shutdowns. The underlying bug is still unresolved; track issue #18330 for updates.
Tags
Getting Started
Download installer
Click the button above to download the installer for your system
Install the software
Double-click the downloaded installer and follow the prompts
Step 1: Download and extract the Druid distribution
Step 2: Run bin/start-druid to start a single-server instance (requires Java 8/11)
Step 3: Open http://localhost:8888 in your browser for the web console
- Step 1: Download and extract the Druid distribution
- Step 2: Run bin/start-druid to start a single-server instance (requires Java 8/11)
- Step 3: Open http://localhost:8888 in your browser for the web console
Checksum not available
This project has not published a SHA-256 checksum on its GitHub Release page
SHA256 Checksum
No checksum available
Download directly from GitHub Releases and verify file integrity yourself
All SHA-256 checksums on this platform are extracted from the project's official GitHub Release page, without any modification. You can independently verify them on the GitHub Releases page.
Open Source Transparency
View GitHub SourceUninstall Info
Stop Druid processes, delete the installation directory and any data directories (default var/ folder). Remove environment variables if set.
No Extra Dependencies
Ready to use after download. No additional runtime required.
Having issues? Check the FAQ below
2 FAQs
Similar Projects
pocketbase
PocketBase is an open source Go backend that includes embedded SQLite with realtime subscriptions, built-in file & user management, admin dashboard UI, and simple REST API. Can be used as standalone app or Go framework.
Visual Studio Code (Code - OSS)
A free, open-source code editor by Microsoft with rich extensions, debugging, and Git integration. The most popular developer tool worldwide.
scrcpy
Display and control your Android device from your computer via USB or TCP/IP. No root required, high performance, low latency, supports audio and video mirroring.