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README
Apache-2.0
QuestDB Logo

 

QuestDB community Slack channel QuestDB open source contributors QuestDB on Apache Maven

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QuestDB

QuestDB is an open-source time-series database for high throughput ingestion and fast SQL queries with operational simplicity.

QuestDB is well-suited for financial market data, IoT sensor data, ad-tech and real-time dashboards. It shines for datasets with high cardinality and is a drop-in replacement for InfluxDB via support for the InfluxDB Line Protocol.

QuestDB implements ANSI SQL with native time-series SQL extensions. These SQL extensions make it simple to filter and downsample data, or 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, C++ and Rust with no dependencies and zero garbage collection.

QuestDB supports schema-agnostic streaming ingestion using the InfluxDB line protocol and a REST API for bulk imports and exports. The QuestDB SQL Web Console is an interactive SQL editor facilitating CSV import. Finally, QuestDB also includes the Postgres Wire Protocol for programmatic queries.

Popular tools that integrate with QuestDB include Apache Kafka, Grafana, Superset, Telegraf and Apache Flink.

Try QuestDB

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 crypto market data with 30M+ rows per month
  • Pos: geolocations of 250k unique ships over time

Checkout our interactive real-time market data dashboards and NYC Taxi Data Analytics Dashboards powered by QuestDB and Grafana.

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

Our demo is running on c5.metal instance and using 24 cores out of 96.

Get started

Install QuestDB

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.

QuestDB Cloud

QuestDB Cloud is the fully managed version of QuestDB, with additional features such as Role-based access control, Cloud-native Replication, Compression, monitoring and cloud-native snapshots. Get started with $200 credits.

Connect to QuestDB

You can interact with QuestDB using the following interfaces:

Insert data

Below are the official QuestDB clients for ingesting data via the InfluxDB Line Protocol:

End-to-end quickstart

Want to walk through everything, from streaming ingestion to visualization with Grafana? Check out our multi-path quickstart repository.

How QuestDB compares to other open source TSDBs

Checkout our benchmark blog post which compares QuestDB and InfluxDB across functionality, maturity and performance.

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

Resources

📚 Read the docs

❓ Get support

🚢 Deploy QuestDB

Contribute

We welcome contributions to the project, whether source code, documentation, bug reports, feature requests or feedback. To get started with contributing:

✨ As a sign of our gratitude, we also send QuestDB swag to our contributors. Claim your swag.

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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QuestDB is a high-performance, open-source SQL database for applications in financial services, IoT, machine learning, DevOps and observability 展开 收起
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