Ignition integrates with InfluxDB

Ignition and InfluxDB combine industrial data acquisition with high-performance time-series storage. While Ignition's built-in historian works with any SQL database, InfluxDB provides optimized storage and retrieval for high-frequency industrial sensor data.

Integration architecture

Ignition connects to InfluxDB through multiple pathways:

• SQL Bridge Module: Log tag data to InfluxDB via JDBC connector
• MQTT/Sparkplug B: Using Cirrus Link modules, Ignition publishes to MQTT broker; Telegraf subscribes and writes to InfluxDB
• REST API: Custom scripts in Ignition call InfluxDB's HTTP API for specialized write patterns

Use cases

• High-frequency data: InfluxDB handles sub-second sampling better than traditional SQL historians
• MING stack deployments: Ignition + Mosquitto + InfluxDB + Grafana forms a complete open-source industrial data pipeline
• Advanced analytics: InfluxDB's Flux query language enables complex time-series analysis beyond Ignition's native capabilities
• Long-term retention: InfluxDB's retention policies and downsampling automate data lifecycle management

Configuration overview

1. Install and configure InfluxDB (authentication, database creation, retention policies)
2. In Ignition, configure SQL Bridge module with InfluxDB JDBC driver
3. Set up transaction groups to log tag data at desired intervals
4. For MQTT path: Install Cirrus Link modules, configure Telegraf with MQTT consumer input

Tradeoffs and considerations

• Query complexity: InfluxDB's Flux language has learning curve versus SQL
• Ecosystem maturity: Fewer third-party tools support InfluxDB compared to PostgreSQL/MySQL
• Operational overhead: Running InfluxDB cluster adds infrastructure complexity
• Integration depth: Native Ignition historian features (deadbanding, store-and-forward) may need custom implementation with InfluxDB