High performance time series database

Superior developer experience with SQL and time series extensions. Speed and reliability to solve ingestion speed bottlenecks.

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Performance

Ingest 2M rows/s per node
Up to 10x faster writes vs InfluxDB
Don’t worry about cardinality
Columnar storage
Data partitioned by time
SIMD-optimized queries

See Benchmarks

Developer experience

Open source under Apache 2.0
Built-in SQL optimizer & REST API
PostgreSQL driver compatibility
InfluxDB Line Protocol API
SQL and time-series joins
Grafana integration

See live demo

Enterprise ready

Cloud & on-prem
Hot & cold read replicas
Role-based access control
Multiple availability zones
Data compression
Enterprise support SLA

See Enterprise

Try the live demo

Query over 2 billion rows in milliseconds in the QuestDB Web Console using SQL

Try QuestDB demo in your browser

See query results >

Use QuestDB with the tools you love

Postgres Grafana Kafka Python Pandas Telegraf Spark Superset MindsDB Cube Redpanda Plotly

Augmented SQL for time series data

ANSI SQL time series extensions made for 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 ON”

Merge Time

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

Transform data into value

Financial market data

Perfect for financial data with time-based ASOF joins and Window functions for moving averages. See our real-time Grafana + QuestDB crypto dashboard. Open source kdb+ alternative.

Application metrics

Track and visualize user behavior data, API calls, data latency, and other application events and analytics in real-time.

Connected devices, IoT

Capture, store and respond to sensor data and telemetry at any resolution in industrial applications—process high cardinality data without hiccups.

Network traffic analysis

Ingest sFlow or other network traffic metadata leveraging QuestDB's native IPv4 type. Detect anomalies in real-time from blasts of networking data.

Machine learning with time series data

Load Pandas DataFrames into QuestDB to the tune of millions of rows per second. Download data from QuestDB to train machine learning models.

AdTech

Monitor user activity by storing and analyzing Ad impressions, clicks, scrolls, and conversions in AdTech platforms.

Peak performance time-series

Hyper ingestion

For massive volumes of time-series data, trust a specialized time-series database. Timestamps are first-class, and blistering throughput is sustained even through the highest data cardinality. Deduplication and out-of-order ingestion also work right out-of-the-box.

Read the docs

“QuestDB outperforms every database we have tested and delivered a 10x improvement in querying speed. It has become a critical piece of our infrastructure.”

Ahmad Abbasi — Co-founder and CEO

A moving average chart for Bitcoin price across several minutes, in different time segments.

What our users say about QuestDB

QuestDB is used at Airbus for real-time applications involving hundreds of millions of data points per day. For us, QuestDB is an outstanding solution that meets (and exceeds) our performance requirements.

>Oliver Pfeiffer
Software Architect, Airbus