Fast SQL for time series

QuestDB is the fastest open source time series database

Query our demo dataset with 1.6 billion rows in milliseconds

docker pull questdb/questdb
docker run -p 9000:9000 questdb/questdb

Built for performance

SIMD-optimized analytics

Row- and column-based access

Vectorized query execution

Tiny memory footprint

C++ and zero-GC Java

A code editor with a chart that shows the result of the query

Optimized for time series

Relational model for time series

Data stored in chronological order

Time partitioned

Immediate consistency

Fast InfluxDB line protocol

A code editor containing a SQL statement

Implemented with SQL

Time series and relational joins

Postgres compatibility

Aggregations and downsampling

Unlimited sub-queries

Built-in SQL optimizer

Integration with the tools you love

Postgres

Grafana

Kafka

Python

Pandas

Telegraf

Tableau

MindsDB

Cube

Plotly

Why QuestDB?

Augmented SQL for time series

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

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;

Search Time

Filter and search for specific timestamps with “WHERE”

Slice Time

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

Navigate Time

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

Merge 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

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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