Optimized for IoT and metrics.
Purpose-built time-series database for IoT, observability, and financial data. Ingest millions of data points per second with automatic downsampling and retention policies.
Millions/sec
Ingest
10:1
Compression
Configurable
Retention
Full support
SQL
Time, optimized.
Purpose-built for IoT and observability.
Time-native queries
Time-bucketing, moving averages, and gap-filling built into the query language.
10:1 compression
Gorilla and delta-of-delta encoding for up to 10× storage savings.
Auto-downsampling
Automatically aggregate old data to reduce storage while preserving trends.
SQL + PromQL
Standard SQL for analytics. PromQL compatibility for Prometheus users.
Continuous aggregates
Materialized views that update automatically as new data arrives.
Grafana native
First-class Grafana datasource for dashboarding and alerting.
Getting started
Launch your first instance in three steps. CLI, console, or API — your choice.
ur db timeseries create metrics \
--retention=90d --size=db-s-4vcpuTime-series patterns.
Infrastructure metrics and IoT sensor data.
Suggested configuration
PromQL · Grafana · Auto-downsample
Estimate your costs
Create detailed configurations to see exactly how much your architecture will cost. Pay for what you use, down to the second.
Configuration 1
Time-Series Engine
Node Resources
Data & Backups
Plan & Commitment
Cost details
Purpose-built for IoT, observability, and financial data.
Works seamlessly with
Frequently asked questions
Time, optimized.
Purpose-built time-series database for IoT and observability.