Efficient PLC Data Logging with InfluxDB: A Comprehensive Guide to Time Series Data Storage

Data logging in PLCs is essential because it enables continuous monitoring and recording of operational data, which is crucial for improving efficiency, reliability, and safety in industrial processes. By capturing key metrics such as temperature, pressure, and system performance over time, data logging helps operators track trends, optimize processes, and detect anomalies early. This not only facilitates preventive maintenance but also aids in troubleshooting by providing a historical record for error analysis and diagnostics. Furthermore, data logging supports regulatory compliance by creating audit trails and ensures quality control through traceability of production processes. Ultimately, it empowers data-driven decision-making, leading to better operational outcomes and enhanced automation.

What is InfluxDB ?

InfluxDB is a high-performance time series database (TSDB) designed specifically for handling time-stamped or time series data, such as metrics, events, and measurements that evolve over time. It's optimized for fast reads and writes of this type of data, making it ideal for applications that need to monitor changes in systems, sensors, devices, or industrial processes over time. InfluxDB offers features like powerful query capabilities, efficient storage, and built-in support for processing time-based data, making it a popular choice in IoT, monitoring, and real-time analytics scenarios.

Why InfluxDB outperforms traditional SQL databases in SCADA systems ?

  1. Optimized for Time Series Data

    2. Unlike traditional SQL databases, InfluxDB is designed specifically for time series data. It stores data with time stamps as a first-class citizen, making it faster and more efficient when dealing with large volumes of time-based data. InfluxDB has native support for data retention policies, allowing automatic purging or downsampling of old data, which helps keep data storage manageable without complex SQL scripts.

  2. High Write and Query Performance

    3. InfluxDB is optimized for high-speed ingestion of time-stamped data, which is crucial for real-time monitoring in SCADA systems. It can handle millions of writes per second, making it suitable for high-frequency data sources such as sensors and PLCs. Time series queries like aggregations, windowing, and downsampling are much faster in InfluxDB compared to traditional SQL databases, which are not inherently optimized for these tasks. This improves performance when analyzing historical trends.

  3. Efficient Data Compression

    4. InfluxDB uses efficient compression algorithms tailored for time series data, reducing storage costs while retaining fast access to historical data. SQL databases typically do not compress time series data as effectively, leading to higher storage usage.

  4. Handling High Cardinality Data

    5. InfluxDB's tag and field system allows for the efficient organization of high cardinality data (such as sensor IDs or device types), enabling quicker access to relevant subsets of data without the overhead of complex SQL joins. It can handle more tags, measurements, and different devices without significant performance degradation, whereas SQL databases may struggle with large volumes of time series data as they grow.

  5. Native Time-Based Functions

    6. InfluxDB provides native support for functions like time bucketing, moving averages, and interpolation, which are common in time series analysis. In SQL, these would require more complex queries, often with performance penalties. InfluxDB allows for continuous queries that automatically compute and store results, such as averages or sums over time, without needing additional coding or manual execution.

  6. Simplified Setup for Time Series Data

    7. InfluxDB integrates seamlessly with SCADA and IoT systems designed for time series data. While SQL databases can be configured for time series, they require more manual effort and are not inherently structured to handle it as efficiently as InfluxDB.

InfluxDB Installation and Setup

To download, install, and set up InfluxDB, you can visit the official InfluxData downloads page at https://portal.influxdata.com/downloads.

How PLC sends data to InfluxDB

To write data to InfluxDB using a POST request, you typically interact with the HTTP API. Below is an outline of the key components of an InfluxDB POST write data request.

Typically to send data from a Siemens PLC to an InfluxDB you shall make use of the TSEND_C function block.

  1. URL

    2. The URL structure for writing data to InfluxDB is:

    POST http://<influxdb-host>:<port>/api/v2/write?org=<organization>&bucket=<bucket>&precision=<precision>

  2. Headers

    3. The request should include the following headers:

    {
  "Authorization": "Token <your-auth-token>",
  "Content-Type": "text/plain"
}

  3. Data Format (Line Protocol)

    4. The body of the POST request should contain data in InfluxDB’s line protocol format:

    measurement,tag1=value1,tag2=value2 field1=value1,field2=value2 <timestamp>

Send PLC data to InfluxDB using Telegraf

Telegraf is an open-source, plugin-driven agent developed by InfluxData that collects, processes, and sends metrics and events from a wide variety of sources to various outputs, including time-series databases like InfluxDB.

To write data from a PLC to InfluxDB using the Telegraf OPC UA plugin, you'll need to set up Telegraf, configure the OPC UA input plugin to read data from your PLC, and then configure the InfluxDB output plugin to write data to your InfluxDB instance.

Where do we go from here?

With a solid understanding of InfluxDB and its advantages for PLC data logging, you might be wondering how to further leverage this powerful tool for your specific needs. The next steps involve deepening your practical knowledge and integration skills. Start by exploring InfluxDB’s extensive documentation and community resources to get acquainted with advanced features and best practices. Consider setting up a test environment to experiment with data ingestion, querying, and visualization. Integrating InfluxDB with your existing SCADA systems can be an effective way to begin implementing real-time data monitoring and analysis. Additionally, learning about InfluxDB’s ecosystem, including tools like Telegraf for data collection and Grafana for visualization, can enhance your data analysis capabilities. Joining forums and engaging with the InfluxDB community can provide valuable insights and support as you refine your implementation. Finally, keep an eye on new updates and features released by InfluxData to stay current with advancements in time series data management.