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Fast SQL for time-series

Columnar time-series database with high performance ingestion and SQL analytics you know and love from QuestDB open source, now on the cloud.

Performance

  • 2M rows/s per node
  • 5-10x faster vs Timescale & InfluxDB
  • Don’t worry about cardinality
  • Columnar storage
  • Data partitioned by time
  • SIMD-optimized queries
See Benchmarks

Developer experience

  • SQL time series extensions
  • Built-in SQL optimizer and REST API
  • PostgreSQL driver compatibility
  • Real-time streaming API
  • SQL and time-series joins
  • Grafana integration
See live demo

Operational simplicity

  • Fully managed hosted cloud
  • Elastic cloud instances
  • TLS for all protocols
  • Online snapshot based backups
  • Monitoring dashboards
  • SSO authentication
See Cloud

See live demo

Query three large datasets and more than 2 billion rows in milliseconds with SQL

Try QuestDB demo in your browser

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Use QuestDB with the tools you love

Postgres logoPostgresGrafana logoGrafanaKafka logoKafkaPython logoPythonPandas logoPandasTelegraf logoTelegrafMindsDB logoMindsDBCube logoCubeRedpanda logoRedpandaPlotlyLogo logoPlotly

Augmented SQL for time series

QuestDB enhances ANSI SQL with time series extensions to manipulate time stamped data

Arrow up icon
SELECT timestamp, tempC
FROM sensors
WHERE timestamp IN '2021-05-14;1M';
-- Search time
SELECT timestamp, tempC
FROM sensors
WHERE timestamp IN '2021-05-14;1M';
SELECT timestamp, avg(tempC)
FROM sensors
SAMPLE BY 5m;
-- Slice time
SELECT timestamp, avg(tempC)
FROM sensors
SAMPLE BY 5m;
SELECT timestamp, sensorName, tempC
FROM sensors
LATEST ON timestamp PARTITION BY sensorName;
-- Navigate time
SELECT timestamp, sensorName, tempC
FROM sensors
LATEST ON timestamp PARTITION BY sensorName;
SELECT sensors.timestamp ts, rain1H
FROM sensors
ASOF JOIN weather;
-- Merge time
SELECT sensors.timestamp ts, rain1H
FROM sensors
ASOF JOIN weather;
Arrow up icon

Magnifying glass iconSearch Time

Filter and search for specific timestamps with “WHERE”

Knife iconSlice Time

Create time buckets and aggregate by intervals with “SAMPLE BY”

Indication arrow iconNavigate Time

Search time series from most recent values to oldest with “LATEST ON”

Two overlapping squaresMerge Time

Join two tables based on timestamp where timestamps do not exactly match with “ASOF JOIN”

Why time series?

DevOps, monitoring and observability

Collect CPU, memory and storage metrics from your infrastructure and get real-time visibility into your entire stack.

Financial market data

Store market tick data to identify historical trends, find correlations and analyze trades in real-time. Build aggregated views across multiple venues and efficiently compute live order books.

Network traffic analysis

Collect sFlow or other network traffic metadata to run analytics and detect anomalies in real-time.

Connected devices

Capture, store and respond to sensor data and telemetry at any resolution in industrial or machine-to-machine applications.

Application metrics

Empower application developers and UX teams to track and visualize user behavior data, API calls, data latency, and other application events in real-time.

Machine learning with time-series data

Use QuestDB with popular Python frameworks and tools for leveraging anomaly detection algorithms, machine learning libraries, statistical analysis with Pandas, or Jupyter notebooks.

Interactive Console

Interactive console to import data (drag and drop) and start querying right away.

Check our Web Console documentation to get started.

Artistic view of QuestDB's Web Console split in 3 components: the navigation tree, the SQL code editor and data displayed as a chart
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Join our developer community

QuestDB is open source. Follow us on Twitter, star our GitHub repo, and join our developer community on Slack!

Go to GitHub  >Join Slack  >
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