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 StarRocks 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 StarRocks 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 StarRocks Breakdown


 
Database Model

Time series database/data historian

Data warehouse

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.

StarRocks can be deployed on-premises, in the cloud, or in a hybrid environment, depending on your infrastructure preferences and requirements.

License

Closed source

Apache 2.0

Use Cases

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

Business intelligence, analytics, real-time data processing, large-scale data storage

Scalability

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

Horizontally scalable, with support for distributed storage and query processing

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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.

StarRocks Overview

StarRocks is an open source high-performance analytical data warehouse that enables real-time, multi-dimensional, and highly concurrent data analysis. It features an MPP (Massively Parallel Processing) architecture and is equipped with a fully vectorized execution engine and a columnar storage engine that supports real-time updates.


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.

StarRocks for Time Series Data

StarRocks is primarily focused on data warehousing workloads but can be used for time series data. StarRocks can be used for real time analytics and historical data analysis.


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.

StarRocks Key Concepts

  • MPP Architecture: StarRocks utilizes an MPP architecture, which enables parallel processing and distributed execution of queries, allowing for high-performance and scalability.
  • Vectorized Execution Engine: StarRocks employs a fully vectorized execution engine that leverages SIMD (Single Instruction, Multiple Data) instructions to process data in batches, resulting in optimized query performance.
  • Columnar Storage Engine: The columnar storage engine in StarRocks organizes data by column, which improves query performance by only accessing the necessary columns during query execution.
  • Cost-Based Optimizer (CBO): StarRocks includes a fully-customized cost-based optimizer that evaluates different query execution plans and selects the most efficient plan based on estimated costs.
  • Materialized View: StarRocks supports intelligent materialized views, which are precomputed summaries of data that accelerate query performance by providing faster access to aggregated 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.

StarRocks Architecture

StarRock’s architecture includes a fully vectorized execution engine and a columnar storage engine for efficient data processing and storage. It also incorporates features like a cost-based optimizer and materialized views for optimized query performance. StarRocks supports real-time and batch data ingestion from a variety of sources and enables direct analysis of data stored in data lakes without data migration

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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.

StarRocks Features

Multi-Dimensional Analysis

StarRocks supports multi-dimensional analysis, enabling users to explore data from different dimensions and perspectives.

High Concurrency

StarRocks is designed to handle high levels of concurrency, allowing multiple users to execute queries simultaneously.

Materialized View

StarRocks supports materialized views, which provide precomputed summaries of data for faster query performance.


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.

StarRocks Use Cases

Real-Time Analytics

StarRocks is well-suited for real-time analytics scenarios, where users need to analyze data as it arrives, enabling them to make timely and data-driven decisions.

Ad-Hoc Queries

With its high-performance and highly concurrent data analysis capabilities, StarRocks is ideal for ad-hoc querying, allowing users to explore and analyze data interactively.

Data Lake Analytics

StarRocks supports analyzing data directly from data lakes without the need for data migration. This makes it a valuable tool for organizations leveraging data lakes for storage and analysis.


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.

StarRocks Pricing Model

StarRocks can be deployed on your own hardware using the open source project. There are also a number of commercial vendors offering managed services to run StarRocks in the cloud.