Data Historian Overview

Data Historian is a high-performance, 64-bit real-time data historian. It is designed for efficient logging, storage, and analysis of industrial and operational data in various industries, particularly in mission-critical environments. It is scalable, robust, and optimized for use in distributed data collection environments. Its capabilities for performance calculation, redundancy, and integration with external systems make it an invaluable tool for enterprises seeking to optimize their data-driven decision-making processes.

Data Historian provides unmatched speed, reliability, and integration for industrial data logging, ensuring both short-term operational efficiency and long-term data management. Its flexibility, combined with advanced data integrity and compression features, makes it an ideal solution for industries requiring robust, scalable, and high-performance data management.

Key features include:

Real-time data collection—Using OPC UA, OPC DA, BACnet, SNMP, and web services to collect data.
High-performance logging—Efficient storage of large data sets using a proprietary high-compression algorithm.
Advanced data analytics—Provides tools for real-time calculations, data aggregation, and performance monitoring.

The benefits of Data Historian include a range of powerful features designed to ensure high performance, scalability, data integrity, and integration with other systems.

The following table describes the key benefits.

Key Benefit	Description
High performance and speed	- Fast data collection—Data Historian can handle over 150,000 data events per second, making it ideal for environments with high-frequency data needs. - Optimized for 64-bit architecture—This allows for more memory usage and faster processing, especially for large-scale or high-speed data collection systems.
Scalability	- Enterprise-wide flexibility—Whether you're managing a small system or an enterprise-level data architecture, Data Historian can scale to meet your needs. It easily adapts to changes, such as the addition of new devices or collectors. - Distributed loggers and collectors—The system supports multiple collectors, either local or remote, which allows data collection to be distributed across different systems for better load management.
Data integrity and redundancy	- Store-and-forward technology—This ensures no data is lost during communication failures. Data is stored locally if the network fails and forwarded when the connection is restored. - Redundant loggers and collectors—Data Historian supports redundancy at both the logger and collector levels, providing continuous data logging even in the event of hardware or software failures.
Efficient data storage and compression	- Swinging Door algorithm—This advanced algorithm reduces data-storage requirements without losing critical information, optimizing storage efficiency. - Archiving—The system allows for automatic archiving, which moves older data to remote storage locations to free up local resources.
Integration and compatibility	- OPC standards compliance—Data Historian supports multiple industrial protocols, such as OPC UA, OPC DA, OPC HDA, SNMP, BACnet, and others. This makes it compatible with a wide range of automation and SCADA systems. - Third-party integration—Data Exporter allows easy data export to systems such as Microsoft SQL Server, Azure Data Lake, Apache Hadoop, and others. - Assets integration—Integrating Data Historian with Assets in GENESIS allows you to harness the power of both tools—Data Historian for high-speed data logging and retrieval and Assets for organizing and visualizing assets linked to real-time or historical data. For more information, refer to Using Historian in Assets.
Data visualization and analysis	- Real-time data replay—Data Historian supports real-time replay of historical data, enabling operators to analyze past events in the context that they occurred. - Performance calculations—The system includes built-in performance calculation functions, allowing for real-time aggregation and analysis of logged data. It supports calculating averages, maximums, and more.
Customization and user-friendly configuration	Adaptable to complex architectures—Whether you're working with single or multi-node systems, Data Historian offers extensive customization options to tailor the system to complex industrial environments.
Long-term data handling	- Efficient archiving and retrieval—Archived data can be easily retrieved for long-term analysis, ensuring compliance with regulatory requirements in industries such as energy or manufacturing. - Data synchronization—Data Historian supports synchronization between multiple loggers, enabling seamless data merging and ensuring consistency across distributed sites.
Cost efficiency	- Optimized storage and data compression—The system reduces storage costs through efficient compression techniques and archiving, which minimizes the need for large-scale data storage solutions. - Low memory footprint—Despite its powerful capabilities, Data Historian has a smaller memory footprint compared to some traditional historians, making it more resource-efficient.
Custom function and calculation support	- You can develop custom .NET C# libraries of functions or calculations that can be processed by Data Historian. - You can customize the calculation functionality of Data Historian while protecting intellectual property at the same time. - Custom calculations can be made as simple or as complex as needed and they support asynchronous processing. - Using standard .Net debugging tools, you can analyze your custom functions or calculations.

The following example explains how to use Data Historian to set up remote collectors to optimize network traffic and data logging.

Example: Remote Data Collection to Reduce Network Load

In a situation where you're collecting data every second from a remote OPC server and calculating the maximum value for every minute, the network load normally involves sending a value every second.

However, by setting up a remote collector on the same machine as the OPC server, only the final calculated value (the maximum for the minute) needs to be sent to the logging server.

This approach significantly reduces network traffic from one value per second to one value per minute.

To set up a remote data collector:

Install Data Historian—Install Data Historian on both the logging server and the remote machine where the OPC server resides.
Synchronize time—Ensure that time has been synchronized on both the logging server and the remote collector machine to prevent data misalignment.
Configure the collector—Open Workbench, and then go to Historical Data > Data Historian > Collectors. Configure the local collector for the remote machine, ensuring that it communicates with the central logging server.

This setup reduces network traffic and ensures efficient, high-performance data collection, making Data Historian especially useful for large, distributed systems.

Other use cases of Data Historian include:

Manufacturing and production: Monitoring equipment performance, product quality, and energy usage in real-time.
Utilities and energy: Logging consumption data and optimizing resource allocation.
Environmental monitoring: Emissions tracking and compliance reporting in heavy industries.