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QuestDB is an open-source time-series database for high throughput ingestion and fast SQL queries with operational simplicity. It supports schema-agnostic ingestion using the InfluxDB line protocol, PostgreSQL wire protocol, and a REST API for bulk imports and exports.
QuestDB is well suited for financial market data, application metrics, sensor data, real-time analytics, dashboards, and infrastructure monitoring.
QuestDB implements ANSI SQL with native time-series SQL extensions. These SQL extensions make it simple to correlate data from multiple sources using relational and time-series joins. We achieve high performance by adopting a column-oriented storage model, parallelized vector execution, SIMD instructions, and low-latency techniques. The entire codebase is built from the ground up in Java and C++, with no dependencies and zero garbage collection.
We provide a live demo provisioned with the latest QuestDB release and sample datasets:
- Trips: 10 years of NYC taxi trips with 1.6 billion rows
- Trades: live crytocurrency market data with 30M+ rows per month
- Pos: geolocations of 250k unique ships over time
Our demo is running on
c5.metal instance and using 24 cores out of 96.
To run QuestDB, Docker can be used to get started quickly:
docker run -p 9000:9000 -p 9009:9009 -p 8812:8812 questdb/questdb
macOS users can use Homebrew:
brew install questdb brew services start questdb questdb start // To start questdb questdb stop // To stop questdb
The QuestDB downloads page provides direct downloads for binaries and has details for other installation and deployment methods.
Connect to QuestDB
You can interact with QuestDB using the following interfaces:
Web Console for interactive
SQL editor on port
InfluxDB line protocol for
high-throughput ingestion on port
REST API on port
PostgreSQL wire protocol on
Below are our official questdb clients for popular programming languages:
How QuestDB compares to other open source TSDBs
This article compares QuestDB to other open source time series databases spanning functionality, maturity and performance.
Here are high-cardinality
Time Series Benchmark Suite
results using the
cpu-only use case with 6 to 16 workers on 32 CPUs and 64GB RAM:
📚 Read the docs
- QuestDB documentation: understand how to run and configure QuestDB.
- Tutorials: learn what's possible with QuestDB step by step.
- Product roadmap: check out our plan for upcoming releases.
❓ Get support
- Community Slack: join technical discussions, ask questions, and meet other users!
- GitHub issues: report bugs or issues with QuestDB.
- Stack Overflow: look for common troubleshooting solutions.
🚢 Deploy QuestDB
We are always happy to have contributions to the project whether it is source code, documentation, bug reports, feature requests or feedback. To get started with contributing:
- Have a look through GitHub issues labeled "Good first issue".
- Read the contribution guide.
- For details on building QuestDB, see the build instructions.
- Create a fork of QuestDB and submit a pull request with your proposed changes.
A big thanks goes to the following wonderful people who have contributed to QuestDB: (emoji key):
This project adheres to the all-contributors specification. Contributions of any kind are welcome!
An open source time-series database for fast ingest and SQL queries
最后更新于 8 hours ago