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 VictoriaMetrics 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 VictoriaMetrics 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 VictoriaMetrics Breakdown
Time series database/data historian
Time series database
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.
VictoriaMetrics can be deployed as a single-node instance for small-scale applications or as a clustered setup for large-scale applications, offering horizontal scalability and replication.
Industrial data management, real-time monitoring, asset health tracking, predictive maintenance, energy management
Monitoring, observability, IoT, real-time analytics, DevOps, application performance monitoring
Supports horizontal scaling through distributed architecture, data replication, and data federation for large-scale deployments
Horizontally scalable, supports clustering and replication for high availability and performance
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.
VictoriaMetrics is an open source time series database developed by the company VictoriaMetrics. The database aims to assist individuals and organizations in addressing their big data challenges by providing state-of-the-art monitoring and observability solutions. VictoriaMetrics is designed to be a fast, cost-effective, and scalable monitoring solution and time series database.
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.
VictoriaMetrics for Time Series Data
VictoriaMetrics is designed for time series data, making it a solid choice for applications that involve the storage and analysis of time-stamped data. It provides high-performance storage and retrieval capabilities, enabling efficient handling of large volumes of time series data.
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.
VictoriaMetrics Key Concepts
- Time Series: VictoriaMetrics stores data in the form of time series, which are sequences of data points indexed by time.
- Metric: A metric represents a specific measurement or observation that is tracked over time.
- Tag: Tags are key-value pairs associated with a time series and are used for filtering and grouping data.
- Field: Fields contain the actual data values associated with a time series.
- Query Language: VictoriaMetrics supports its own query language, which allows users to retrieve and analyze time series data based on specific criteria.
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.
VictoriaMetrics is available in two forms: Single-server-VictoriaMetrics and VictoriaMetrics Cluster. The Single-server-VictoriaMetrics is an all-in-one binary that is easy to use and maintain. It vertically scales well and can handle millions of metrics per second. On the other hand, VictoriaMetrics Cluster consists of components that allow for building horizontally scalable clusters, enabling high availability and scalability in demanding environments. The architecture of VictoriaMetrics enables users to choose the deployment option that best suits their needs and scale their database infrastructure as required.
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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.
The PI System is highly scalable, allowing organizations to handle large volumes of data and a growing number of data sources without compromising performance.
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.
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.
VictoriaMetrics is optimized for high-performance storage and retrieval of time series data. It can efficiently handle millions of metrics per second and offers fast query execution for real-time analysis.
The architecture of VictoriaMetrics allows for both vertical and horizontal scalability, enabling users to scale their monitoring and time series database infrastructure as their data volume and demand grow.
VictoriaMetrics provides a cost-effective solution for managing time series data. Its efficient storage and query capabilities contribute to minimizing operational costs while maintaining high performance.
OSI PI Data Historian Use Cases
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.
By analyzing historical data and detecting patterns or anomalies, OSI PI enables organizations to implement predictive maintenance strategies, reducing equipment downtime and maintenance costs.
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.
VictoriaMetrics Use Cases
Monitoring and Observability
VictoriaMetrics is widely used for monitoring and observability purposes, allowing organizations to collect, store, and analyze metrics and performance data from various systems and applications. It provides the necessary tools and capabilities to track and visualize key performance indicators, troubleshoot issues, and gain insights into system behavior.
IoT Data Management
VictoriaMetrics is suitable for handling large volumes of time series data generated by IoT devices. It can efficiently store and process sensor data, enabling real-time monitoring and analysis of IoT ecosystems. VictoriaMetrics allows for tracking and analyzing data from factories, manufacturing plants, satellites, and other IoT devices.
VictoriaMetrics enables retrospective analysis and forecasting of metrics for capacity planning purposes. It allows organizations to analyze historical data, identify patterns and trends, and make informed decisions about resource allocation and future capacity requirements.
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.
VictoriaMetrics Pricing Model
VictoriaMetrics is an open source project, which means it is available for free usage and doesn’t require any licensing fees. Users can download the binary releases, Docker images, or source code to set up and deploy VictoriaMetrics without incurring any direct costs. VictoriaMetrics also has paid offerings for on-prem Enterprise products and managed VictoriaMetrics instances.
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