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InfluxDB

InfluxDB: High-throughput time-series database

What it’s for: High-volume metrics including IoT sensors, industrial monitoring, and sub-second precision data.

Trade-offs

ProsCons
Very high write throughputDifferent ecosystem than Prometheus
Three query languages: SQL, InfluxQL, FluxStorage grows quickly
Built-in downsamplingLearning curve for either language
Strong retention policiesCloud version can be expensive

Query language support by version

InfluxDB VersionQuery Languages
3.x / Cloud ServerlessSQL, InfluxQL, Flux
2.xInfluxQL, Flux
1.xInfluxQL, Flux

Best for

  • IoT and sensor data
  • Industrial monitoring
  • High-frequency metrics (sub-second)

Documentation

View the full documentation. Learning path coming soon!

InfluxDB data source

Script

InfluxDB is the other major player in time-series databases, and it has a different sweet spot than Prometheus. Where Prometheus excels at cloud-native metrics with its pull model, InfluxDB shines at high write throughput, pushing millions of data points per second. Think IoT sensors, industrial monitoring, high-frequency trading systems.

You have three query language options depending on your version: SQL for InfluxDB 3.x, InfluxQL which is SQL-like with familiar SELECT, FROM, and WHERE statements, and Flux which is functional with broader capabilities for data shaping and transformations. InfluxDB also has built-in downsampling and retention policies, which helps manage storage as data ages.

If you’re dealing with massive volumes of time-series data from devices or sensors, InfluxDB is worth considering.

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