Choosing the right database is a critical choice when building any software application. All databases have different strengths and weaknesses when it comes to performance, so deciding which database has the most benefits and the most minor downsides for your specific use case and data model is an important decision. Below you will find an overview of the key concepts, architecture, features, use cases, and pricing models of OSI PI Data Historian and OpenTSDB so you can quickly see how they compare against each other.

The primary purpose of this article is to compare how OSI PI Data Historian and OpenTSDB perform for workloads involving time series data, not for all possible use cases. Time series data typically presents a unique challenge in terms of database performance. This is due to the high volume of data being written and the query patterns to access that data. This article doesn’t intend to make the case for which database is better; it simply provides an overview of each database so you can make an informed decision.

OSI PI Data Historian vs OpenTSDB Breakdown


 
Database Model

Time series database/data historian

Time series database

Architecture

OSIsoft PI System is a suite of software products designed for real-time data collection, storage, and analysis of time series data in industrial environments. The PI System is built around the PI Server, which stores, processes, and serves data to clients, and it can be deployed on-premises or in the cloud.

OpenTSDB can be deployed on-premises or in the cloud, with HBase running on a distributed cluster of nodes.

License

Closed source

GNU LGPLv2.1

Use Cases

Industrial data management, real-time monitoring, asset health tracking, predictive maintenance, energy management

Monitoring, observability, IoT, log data storage

Scalability

Supports horizontal scaling through distributed architecture, data replication, and data federation for large-scale deployments

Horizontally scalable across multiple nodes using HBase as its storage backend

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OSI PI Data Historian Overview

OSI PI, also known as OSIsoft PI System, is an enterprise-level data management and analytics platform specifically designed for handling time series data from industrial processes, sensors, and other sources. Developed by OSIsoft (acquired by AVEVA in 2021), the PI System has been widely used in various industries such as energy, manufacturing, utilities, and pharmaceuticals since its introduction in the 1980s. It provides the ability to collect, store, analyze, and visualize large volumes of time series data in real-time, allowing organizations to gain insights, optimize processes, and improve decision-making.

OpenTSDB Overview

OpenTSDB (Open Time Series Database) is an open-source, distributed, and scalable time series database built on top of Apache HBase, a NoSQL database. OpenTSDB was designed to address the growing need for storing and processing large volumes of time series data generated by various sources, such as IoT devices, sensors, and monitoring systems. It was initially developed by StumbleUpon in 2010 and later became an independent project with an active community of contributors.


OSI PI Data Historian for Time Series Data

OSI PI was created for storing time series data, making it an ideal choice for organizations that need to manage large volumes of sensor and process data. Its architecture and components are optimized for collecting, storing, and analyzing time series data with high efficiency and minimal latency. The PI System’s scalability and performance make it a suitable solution for organizations dealing with vast amounts of data generated by industrial processes, IoT devices, or other sources.

OpenTSDB for Time Series Data

OpenTSDB is designed for time series data storage and analysis, making it an ideal choice for managing large scale time series datasets. Its architecture enables high write and query performance, and it can handle millions of data points per second with minimal resource consumption. OpenTSDB’s flexible querying capabilities allow users to perform complex analysis on time series data efficiently.


OSI PI Data Historian Key Concepts

  • PI Server: The core component of the PI System, responsible for data collection, storage, and management.
  • PI Interfaces and PI Connectors: Software components that collect data from various sources and send it to the PI Server.
  • PI Asset Framework: A modeling framework that allows users to create a hierarchical structure of assets and their associated metadata, making it easier to understand and analyze data.
  • PI DataLink: An add-in for Microsoft Excel that enables users to access and analyze PI System data directly from Excel.
  • PI ProcessBook: A visualization tool for creating interactive, graphical displays of PI System data.

OpenTSDB Key Concepts

  • Data Point: A single measurement in time consisting of a timestamp, metric, value, and associated tags.
  • Metric: A named value that represents a specific aspect of a system, such as CPU usage or temperature.
  • Tags: Key-value pairs associated with data points that provide metadata and help categorize and query the data.


OSI PI Data Historian Architecture

OSI PI is a data management platform built around the PI Server, which is responsible for data collection, storage, and management. The PI System uses a highly efficient, proprietary time series database to store data. PI Interfaces and PI Connectors collect data from various sources and send it to the PI Server. The PI Asset Framework (AF) allows users to model their assets and their associated data in a hierarchical structure, making it easier to understand and analyze the data. Various client tools, such as PI DataLink and PI ProcessBook, enable users to access and visualize data stored in the PI System.

OpenTSDB Architecture

OpenTSDB is built on top of Apache HBase, a distributed and scalable NoSQL database, and relies on its architecture for data storage and management. OpenTSDB stores time series data in HBase tables, with data points organized by metric, timestamp, and tags. The database uses a schema-less data model, which allows for flexibility when adding new metrics and tags. The OpenTSDB architecture also supports horizontal scaling by distributing data across multiple HBase nodes.

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OSI PI Data Historian Features

Data collection and storage

OSI PI’s PI Interfaces and PI Connectors enable seamless data collection from a wide variety of sources, while the PI Server efficiently stores and manages the data.

Scalability

The PI System is highly scalable, allowing organizations to handle large volumes of data and a growing number of data sources without compromising performance.

Asset modeling

The PI Asset Framework (AF) provides a powerful way to model assets and their associated data, making it easier to understand and analyze complex industrial processes.

Data visualization

Tools like PI DataLink and PI ProcessBook enable users to analyze and visualize data stored in the PI System, facilitating better decision-making and process optimization.

OpenTSDB Features

Scalability

OpenTSDB’s distributed architecture allows for horizontal scaling, ensuring that the database can handle growing volumes of time series data.

Data Compression

OpenTSDB uses various compression techniques to reduce the storage footprint of time series data.

Query Language with time series support

OpenTSDB features a flexible query language that supports aggregation, downsampling, filtering, and other operations for analyzing time series data.


OSI PI Data Historian Use Cases

Process optimization

OSI PI can help organizations identify inefficiencies, monitor performance, and optimize their industrial processes by providing real-time insights into time series data from sensors and other sources.

Predictive maintenance

By analyzing historical data and detecting patterns or anomalies, OSI PI enables organizations to implement predictive maintenance strategies, reducing equipment downtime and maintenance costs.

Energy management

OSI PI can be used to track energy consumption across various assets and processes, allowing organizations to identify areas for improvement and implement energy-saving measures.

OpenTSDB Use Cases

Monitoring and Alerting

OpenTSDB is well-suited for large-scale monitoring and alerting systems that generate vast amounts of time series data from various sources.

IoT Data Storage

OpenTSDB can store and analyze time series data generated by IoT devices, such as sensors and smart appliances, enabling real-time insights and analytics.

Performance Analysis

OpenTSDB’s flexible querying capabilities make it an ideal choice for analyzing system and application performance metrics over time.


OSI PI Data Historian Pricing Model

Pricing for OSI PI is typically based on a combination of factors such as the number of data sources, the number of users, and the level of support required. Pricing details are not publicly available, as they are provided on a quote basis depending on the specific needs of the organization.

OpenTSDB Pricing Model

OpenTSDB is open-source software, which means it is free to use without any licensing fees. However, the cost of running OpenTSDB depends on the infrastructure required to support the underlying HBase database, such as cloud services or on-premises hardware.