MODHIST (Modern Data Historian for Industrial Data Fabric Component) is a modern data historian concept for industrial digital platforms, based on new distributed and time-series data-oriented software technologies.

MODHIST aims to access and integrate data collected from industrial processes to improve and make faster data-driven process decisions. Typically, a data historian writes and reads streaming time series data in production, collecting real-time process data from process control systems, sensors, equipment, and other data. The goal of this type of solution is to support analytics and decision-making and digital transformation by storing data on-site, in the cloud, on the edge, or in a data lake, for an enterprise.

MODHIST is a software system that records and retrieves production and process data by time; it stores the information in a time-series database that can store data efficiently with minimal disk space and fast retrieval of information. Time series information is often displayed in a trend or as tabular data over a range of time (e.g., last day, last 8 hours, last year, etc.). MODHIST offers much higher levels of efficiency than other data historian systems could offer with more traditional technology.

MODHIST is based widely known open source for connectivity and data ingestion (through MQTT Broker), data processing (through data processing pipelines), and data storage for a high volume of event data (through a time series database). MODHIST is compatible with other visualization tools (such as Apache Grafana) so that data stored in the database can be visualized with 3rd party tools.

To be able to run MODHIST, it is recommended to have generic two machines with a Linux-based Operative System installed (CentOS 7 recommended), each with a minimum of 1 CPU 3,0 GHz and 2GB of RAM. Both machines need to have Docker[1] and Docker-compose[2] utilities installed.

[1] Docker –

[2] Docker-compose

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Posted on

January 30, 2023