Useful Data Tips

TimescaleDB

⏱️ 8 sec read 🗄️ Data Management

What it is: PostgreSQL extension for time-series data. Get time-series performance while keeping full SQL, joins, and ACID guarantees.

What It Does Best

Full SQL support. Unlike purpose-built time-series databases, you keep all PostgreSQL features. JOINs, CTEs, window functions.

Automatic partitioning. Hypertables automatically partition by time. Query optimization and data management handled.

Compression. Native columnar compression. 90%+ compression ratios on time-series data.

Key Features

Hypertables: Automatic time-based partitioning at scale

Compression: Native columnar compression for old data

Continuous aggregates: Materialized views that update automatically

Data retention: Automatic data lifecycle management

Full PostgreSQL: All Postgres features plus time-series optimizations

Pricing

Open Source: Free, Apache 2.0 license (self-hosted)

Timescale Cloud: $0.50/GB-month storage, $0.10/million rows written

Free tier: 30-day trial with credits

Self-hosted: Free on your PostgreSQL instance

When to Use It

✅ Time-series + relational data together

✅ Need SQL and existing PostgreSQL ecosystem

✅ IoT, metrics, financial tick data

✅ Already using PostgreSQL

✅ Want SQL power with time-series performance

When NOT to Use It

❌ Extreme write throughput (InfluxDB better)

❌ Don't need SQL (InfluxDB simpler)

❌ Multi-model data (consider Couchbase)

❌ Pure time-series without relational (InfluxDB specialized)

❌ Not already on PostgreSQL (learning curve)

Common Use Cases

IoT analytics: Sensor data with device metadata in relational tables

Financial data: Tick data with reference data lookups

Monitoring: Application metrics combined with config data

Industrial data: Equipment telemetry with asset management

Energy/utilities: Smart meter data at scale

TimescaleDB vs Alternatives

vs InfluxDB: TimescaleDB has SQL and relational, InfluxDB faster for pure time-series

vs PostgreSQL: TimescaleDB optimized for time-series, much better performance

vs Prometheus: TimescaleDB long-term storage, Prometheus better for metrics scraping

Unique Strengths

PostgreSQL compatibility: Full SQL with time-series performance

Relational + time-series: JOIN time-series with reference data easily

Ecosystem access: Use all PostgreSQL tools and extensions

Compression: Store 20x more data than vanilla Postgres

Bottom line: Best time-series database if you value SQL. Keep PostgreSQL benefits, gain time-series optimizations. Perfect middle ground between InfluxDB's speed and PostgreSQL's flexibility.

Visit TimescaleDB →

← Back to Data Management Tools