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QuestDB is an open source time-series database for fast ingest and SQL queries

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QuestDB open source contributors QuestDB on Apache Maven

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QuestDB is the fastest growing open-source time-series database offering blazingly fast, high throughput ingestion and dynamic, low-latency SQL queries. The entire high-performance codebase is built from the ground up in Java, C++ and Rust with no dependencies and zero garbage collection.

We achieve high performance via a column-oriented storage model, parallelized vector execution, SIMD instructions, and low-latency techniques. In addition, QuestDB is hardware efficient, with quick setup and operational efficiency.

QuestDB implements ANSI SQL with native time-series SQL extensions. These SQL extensions make it simple to analyze, filter and downsample data, or to correlate data from multiple sources using relational and time-series joins.

Ready to go? Jump to the Get started section.

 

QuestDB Web Console showing a SQL statement and query result

QuestDB Web Console - click to launch demo

 

Benefits of QuestDB

QuestDB excels with:

  • financial market data
  • IoT sensors with high data cardinality
  • real-time dashboards

Feature highlights include:

  • SQL with powerful, SIMD-optimized time-series extensions
  • High-speed ingestion via the InfluxDB Line Protocol
  • Strong and efficient performance on limited hardware
  • Columnar storage format (native or Apache Parquet), partitioned and ordered by time
  • Responsive and intuitive Web Console for query and data management, with error handling
  • Excellent performance with high data cardinality - see benchmarks

And why use a time-series database?

Beyond performance and efficiency, with a specialized time-series database, you don't need to worry about:

  • out-of-order data
  • duplicates
  • exactly one semantics
  • streaming data (low latency)
  • high volumes of concurrent requests
  • volatile and "bursty" data
  • adding new columns - change schema "on the fly" while streaming data

Try QuestDB, demo and dashboards

The live, public demo is provisioned with the latest QuestDB release and sample datasets:

  • Trips: 10 years of NYC taxi trips with 1.6 billion rows
  • Trades: live crypto market data with 30M+ rows per month
  • Pos: geolocations of 250k unique ships over time

Use example queries or write your own!

The public demo queries over 1.6BN rows and uses a r6a.12xlarge 48 vCPU and 348GB RAM instance.

Query Execution time
SELECT sum(double) FROM trips 0.15 secs
SELECT sum(double), avg(double) FROM trips 0.5 secs
SELECT avg(double) FROM trips WHERE time in '2019' 0.02 secs
SELECT time, avg(double) FROM trips WHERE time in '2019-01-01' SAMPLE BY 1h 0.01 secs
SELECT * FROM trades LATEST ON timestamp PARTITION BY symbol 0.00025 secs

We also have some public, real-time demo dashboards using our Grafana-native plugin:

QuestDB performance vs. other oss databases

QuestDB performs very well in performance benchmarks compared to alternatives.

For deep dives into internals and performance, see the following blog posts:

As always, we encourage you to run your own benchmarks.

A chart comparing the ingestion rate of QuestDB, InfluxDB and TimescaleDB.

Get started

Use Docker to start quickly:

docker run -p 9000:9000 -p 9009:9009 -p 8812:8812 questdb/questdb

Or macOS users can use Homebrew:

brew install questdb
brew services start questdb
questdb start
questdb stop

Alternatively, to kickoff the full onboarding journey, start with our concise quick start guide.

First-party ingestion clients

QuestDB clients for ingesting data via the InfluxDB Line Protocol:

Connect to QuestDB

Interact with QuestDB and your data via the following interfaces:

Popular third-party tools

Popular tools that integrate with QuestDB include:

End-to-end code scaffolds

From streaming ingestion to visualization with Grafana, start with code scaffolds in from our quickstart repository.

Configure QuestDB for production workloads

Find our capacity planning to fine-tune QuestDB for production workloads.

QuestDB Enterprise

For secure operation at greater scale or within larger organizations.

Additional features include:

  • multi-primary ingestion
  • read replica(s)
  • cold storage integration
  • role-based access control
  • TLS encryption
  • native querying of Parquet files via object storage
  • support SLAs, enhanced monitoring and more

Visit the Enterprise page for further details and contact information.

Additional resources

📚 Read the docs

❓ Get support

🚢 Deploy QuestDB

Contribute

Contributions welcome!

We appreciate:

To get started with contributing:

✨ As a sign of our gratitude, we send QuestDB swag to our contributors!

A big thanks goes to the following wonderful people who have contributed to QuestDB emoji key:


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This project adheres to the all-contributors specification. Contributions of any kind are welcome!

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