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Using InfluxDB for Industrial Data Collection and Comparison with MongoDB

Authors
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    Name
    Martin Szerment

Introduction

Collecting data in industry requires appropriate database systems capable of handling large amounts of real-time generated data. InfluxDB and MongoDB are two popular solutions used in such scenarios. In this article, we will discuss when it is worth using InfluxDB and when MongoDB is a better choice, highlighting their advantages and limitations in the context of industrial data.

InfluxDB – A Specialized Database for Time-Series Data

What is InfluxDB?

InfluxDB is a database optimized for storing and analyzing time-series data. These data are continuously collected, timestamped, and often represent parameters such as:

  • Temperature,
  • Vibrations,
  • Rotational speed,
  • Energy consumption.

Advantages of InfluxDB:

  1. Optimization for Time-Series Data:

    • InfluxDB stores data in columns, which speeds up read operations and real-time data analysis.
    • Built-in support for time-stamps allows for fast querying of trends and historical analysis.

  2. Advanced Query Functions:

    • Supports analytical queries (e.g., average, minimum, maximum, standard deviation) without needing external tools.

  3. Low Memory Requirements:

    • Data can be automatically aggregated and compressed, reducing their size.

  4. Support for IoT and Industrial Systems:

    • InfluxDB integrates with many industrial systems such as MQTT, OPC UA, and SCADA.

Use of InfluxDB in Industry:

  • Machine Monitoring: Continuous recording of operational parameters such as pressure or temperature.
  • Trend Analysis: Detecting anomalies in real time based on historical data.
  • Failure Prediction: Collaborating with predictive algorithms (e.g., TensorFlow, PyTorch) to predict failure states.

MongoDB – A Universal Document Database

What is MongoDB?

MongoDB is a non-relational document database that stores data in JSON or BSON format. It is a versatile solution often used for various types of data, including:

  • Transactional data,
  • Structured and unstructured data,
  • IoT system data.

Advantages of MongoDB:

  1. Flexibility:

    • It can store data with varying structures in a single collection.

  2. Ease of Integration:

    • MongoDB integrates well with web applications and industrial systems.

  3. Support for Large Data Sets:

    • MongoDB can handle massive amounts of data, distributing them across multiple nodes.

  4. Versatility:

    • It can store time-series data, but it is not optimized for that purpose.

Use of MongoDB in Industry:

  • Storing Machine Data: Information about machine types, configurations, and repair history.
  • Storing IoT Data: MongoDB can store data from IoT devices like sensors or controllers.
  • MES Systems: MongoDB is used as a central database in manufacturing execution systems.

Comparison of InfluxDB and MongoDB

CriterionInfluxDBMongoDB
Type of DataTime-series dataUniversal, document-based data
OptimizationOptimized for time-series data storage and analysisFlexible, but not optimized for time-series data
Query SpeedVery fast for time-series dataFast, but depends on the data structure
Data AggregationBuilt-in aggregation functions for trend analysisRequires additional tools (e.g., aggregators)
Use CasesMachine monitoring, trend analysis, IoTStoring IoT data, MES systems, transactional data
ScalabilityExcellent, but mainly for time-series dataExcellent, universal scalability
Ease of UseSpecialized for time-series data expertsEasy integration with various application types

When to Choose InfluxDB?

  1. Time-Series Data: When your data is timestamped, such as machine sensor data (e.g., temperature, vibrations).
  2. Continuous Monitoring: Ideal for systems requiring real-time data analysis.
  3. IoT and Industry 4.0: In IoT scenarios where data arrives at regular intervals.

When to Choose MongoDB?

  1. Varied Data Structures: When your data is diverse, such as machine metadata, configuration data, and reports.
  2. Integration with MES Systems: MongoDB works well for storing system data in manufacturing execution systems.
  3. Universal Needs: When you need to store more than just time-series data.

Summary

InfluxDB and MongoDB are powerful tools, but each has its specific use case:

  • InfluxDB is indispensable for collecting and analyzing time-series data from industrial machines, particularly in IoT and Industry 4.0 applications.
  • MongoDB offers greater flexibility and is more universal, making it suitable for manufacturing management systems and storing unstructured data.

Choosing the right tool depends on the data characteristics and project requirements. Long-term solutions often use both databases, leveraging their strengths in different areas.

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