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Data Historian

A Data Historian is a type of software specifically designed for capturing and storing time-series data from industrial operations.

What is a Data Historian?

A Data Historian is a type of software specifically designed for capturing and storing time-series data from industrial operations. Time series data includes sequential measurements taken from the same source over a defined period of time. It could be anything from the temperature of an industrial refrigerator every five minutes to the pressure levels in a gas pipeline recorded every second.

Data historians are a key part of the Industrial IoT ecosystem, where numerous devices and systems generate continuous streams of data. These programs collect, store, and retrieve data at high speeds, enabling real-time process tracking, monitoring, and analysis.

Data from historians is used to improve process efficiency, predict equipment failures, monitor energy usage, and comply with regulatory requirements. Data Historians are key in various industries including oil and gas, power generation, manufacturing, and pharmaceuticals.

Data historian benefits

Data historians offer a number of benefits for storing the types of data generated by industrial equipment. In this section we’ll look at some of the biggest benefits.


Because data historians are optimized for working with time series data they provide better performance compared to a more general purpose database. This means you will be able to query data faster and also write data at higher volumes without requiring as much hardware to scale.

Cost savings

In the same way data historians provide better performance, they also enable cost savings because they can get the same work done with fewer hardware resources required. A specific example would be that data historians are able to get higher compression ratios on time series data which results in less storage space being needed. Many data historians will also provide functionality that allows you to run your system with fewer engineers being needed, further reducing costs.

Regulatory compliance

Some industries require retaining data for long periods of time for auditing and reporting purposes. A data historian will make this task easy to accomplish.

Higher efficiency

Data historians enable things like predictive maintenance and real time analytics which can be used to make your business more efficient and reduce downtime.

Data historian use cases


In a manufacturing setting, data historians can monitor machine efficiency and productivity, allowing for identification of bottlenecks and inefficiencies. Predictive maintenance use cases can foresee potential machine breakdowns, minimizing downtime.

Oil and gas

Data historians help track the performance of drilling rigs, pipelines, and other equipment. Predictive analysis can identify potential issues, while historical data can assist in decision-making processes and improve safety measures.

Transportation and logistics

Historians can track and analyze data from various sensors in vehicles and equipment, improving maintenance scheduling, fuel efficiency, and overall fleet management.


Data historians track and analyze energy consumption data, helping identify inefficiencies and opportunities for cost savings. Additionally, they can monitor equipment status in real-time, predict potential outages, and enable rapid response.

Data historian features

Let’s take a look at some features commonly provided by data historians:

  • Scalability - A data historian should be able to easily scale horizontally to handle larger volumes of data over time without requiring extra effort from your engineering team
  • Interoperability- A big challenge with industrial IoT is the large number of devices from different vendors that often communicate in different protocols. A historian should provide integration and interoperability out of the box.
  • Data security- Historians should have a number of options for security and be able to be fine tuned for specific use cases.
  • Query speed and write throughput - Time series data is usually generated in large volumes and has unique query patterns that general databases struggle with. Performance in terms of query speed and write throughput should be a top priority for a data historian.
  • Data analysis and forecasting - Some data historians will provide functionality for analyzing data and creating forecasts so you don’t have to rely on external tools.
  • Developer experience - Data historians should provide a solid developer experience that enables engineers and analysts working with them to be productive.

InfluxDB as a data historian

Many companies across different industries are using InfluxDB as their data historian. As a time series database, InfluxDB provides the performance required in addition to scalability and data compression.

InfluxData also offers Telegraf, which makes integrating your systems with InfluxDB easy. Telegraf has over 300 different plugins which allow you to connect to different devices or protocols and forward the data to InfluxDB or other data stores. Telegraf also has the ability to transform or filter data before sending it to storage.


What are the requirements for process manufacturing?

Process manufacturing refers to the production of goods that are produced in large quantities by following a specific formula or recipe. Requirements for process manufacturing include accurate measurement and monitoring of production data. The right data historian should, therefore, be able to capture and store plant data in real-time, support OPC interfaces, and provide advanced features such as data compression and retrieval.

What is an enterprise data historian?

An enterprise data historian is a data historian that focuses on providing data management and data analysis across different levels of an organization. It enables managers and other stakeholders to access data from multiple sources in real-time and make informed decisions based on accurate and reliable data.

What is the difference between a data historian and a time series database?

A data historian is a type of database that is specifically designed to store and manage time-stamped data from industrial and process manufacturing environments. A time series database, on the other hand, is designed to store time-stamped data from a wide variety of sources, including Internet of Things (IoT) sensors, financial markets, and more. While the two technologies share some similarities, data historians typically have features that are tailored for industrial data and process manufacturing.

What is the purpose of a database in the industrial process?

Databases in industrial processes are used to store and manage data that is generated by equipment, sensors, and other sources. The data stored in these databases is used to monitor the performance of industrial processes, identify potential issues or bottlenecks, and optimize processes for maximum efficiency. Industrial databases allow manufacturing and process engineers to gather detailed data about their operations, helping them to improve safety, quality, and productivity.

What is an operational historian?

An operational historian is a type of database that is used to store and manage real-time data from industrial processes as it is generated. Operational historians are designed for use in applications where fast access to data is critical, such as in control systems and other real-time applications.

What is the difference between a data historian and a traditional relational database?

Data historians are designed specifically for time-stamped and event-based data, while relational databases are better suited for structured data such as that found in financial applications or CRM software. Data historians provide additional features such as advanced data storage and compression optimized for time series data, support for analog data, and visual presentations of the data, among others.

What types of data are stored in a data historian?

Data historians are most commonly used to store time-series data, such as data that changes over time and is generated by industrial or manufacturing processes. This data can include analog data, digital data, and event data. Historians are used to store data that is generated by machines and processes, such as temperature readings, process variables, and other metrics.

How is data generated by equipment and sensors collected and stored in a historian?

Data from equipment and sensors is typically collected and sent to the historian using a variety of protocols and methods, such as OPC UA, Modbus, or a proprietary protocol. Once the data is received, the historian stores it in a raw format, either in memory or on disk. Data is then compressed and archived to save space and improve retrieval times. Data management software is typically used to interact with the historian, allowing users to retrieve and analyze data directly.

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