Compare PI System with TDengine

For organizations evaluating alternatives to AVEVA PI System, the decision goes beyond time-series data storage. Asset modeling, real-time analytics, integration, and migration effort all play an important role. This article compares PI System with TDengine, a modern alternative to traditional data historians, to help you evaluate the right solution for your industrial data infrastructure.

About AVEVA PI System

PI System, originally developed by OSIsoft and now part of AVEVA, is one of the most widely used industrial data infrastructure platforms for collecting, storing, and organizing time-series data from sensors, equipment, and control systems. It is designed to integrate data from thousands of sources in real time, create contextual models of industrial operations, and deliver this information to operators, engineers, and business systems for monitoring and analysis.

About TDengine

TDengine is a modern alternative to traditional data historians such as AVEVA PI System. It combines TDengine TSDB, a high-performance time-series database, with TDengine IDMP, an AI-native industrial data management platform.

TDengine TSDB handles industrial data ingestion, storage, querying, and real-time processing, while TDengine IDMP enables asset modeling, data contextualization, visualization, real-time analytics, and AI-powered applications. Together, they help industrial teams go beyond traditional historian capabilities to understand their operations, investigate events, and make better use of industrial data

Which Is Best for You?

PI System and TDengine support many of the same industrial use cases, including operational monitoring, asset modeling, real-time analysis, and data sharing with other applications. However, they differ in pricing, deployment flexibility, AI capabilities, ecosystem openness, and approaches to modernization. The following sections highlight the key differences to consider when evaluating a PI System alternative.

1. Pricing model

   • PI System prices are not publicly available, forcing customers to meet with the sales team just to know how much to budget. AVEVA no longer provides perpetual licenses, instead requiring customers to purchase its Flex credits in order to use PI System and other services. Some products are sold by seat, meaning that costs increase as teams grow. Finally, many critical components such as PI Interfaces, PI DataLink, and PI Vision are sold separately from the core PI System.

   • TDengine All-in-One offers transparent, publicly available pricing, with annual and perpetual licensing options. For self-hosted deployments with up to 5,000 tags, TDengine All-in-One, including TDengine IDMP, is free forever. Larger deployments can choose flexible licensing options based on tag count, with optional support and high-availability services. This makes TDengine an attractive and cost-effective alternative for organizations looking to modernize their industrial data infrastructure.

2. Cloud support

   • PI System was originally designed for on-premises industrial environments, with core server components built around Windows. While PI System can be deployed in cloud environments and integrated with AVEVA’s cloud services, these approaches may introduce additional architectural and integration considerations when managing industrial data across multiple sites.

   • TDengine is designed for flexible deployment across industrial environments. Organizations can deploy TDengine All-in-One at the edge, on-premises, or in public, private, and hybrid clouds. TDengine Cloud is also available as a fully managed service on AWS, Azure, and Google Cloud. This flexibility allows industrial teams to maintain a consistent data platform across different sites and deployment environments.

3. AI integration

   • The core PI System does not include native AI or LLM capabilities, and customers that want AI-driven analysis need to integrate with external analytics tools or platforms. This requires development effort on the part of the customer to set up data pipelines, cleansers, and connections, increasing the IT burden on industrial enterprises.

   • TDengine brings AI directly into industrial data workflows. With built-in AI capabilities, users can ask questions about their industrial data in natural language, generate dashboards and analyses, and receive AI-powered explanations of operational trends. TDengine’s Zero-Query Intelligence can also generate visualizations and analysis tasks without requiring users to write prompts or queries. TDengine also supports AI-assisted root-cause analysis, helping engineers investigate events, identify patterns, and explore potential causes using real industrial data.

     In addition, TDengine provides built-in time-series forecasting and anomaly detection through TDgpt, along with AI skills for common industrial analysis tasks. These capabilities help teams move beyond traditional historian reporting toward more proactive and AI-assisted industrial operations.

4. Data sharing:

   • With PI System and AVEVA CONNECT data services, you can create custom views to define the granularity of shared data, ensuring security and compliance while giving key stakeholders and applications access to needed information. For programmatic integration, PI System provides PI Web API and SDKs, although connecting downstream applications may still require additional development effort.

   • In addition to traditional views, TDengine offers data sharing on a publish-subscribe (pub-sub) model with its data subscription feature, in which applications are notified whenever new data points are inserted into TDengine. Data subscription in TDengine can use a Kafka-like protocol or standard MQTT. This model is better suited for data-intensive AI and other real-time analytics applications than traditional view-based sharing.

5. Ecosystem: Although offering many of the same features for many of the same business scenarios, the two products differ on a fundamental level. Due to the closed nature of AVEVA products, PI System customers’ choices are more limited in terms of system interoperability and expansion.

   TDengine takes a more open approach. Built on the open-source TDengine TSDB, the platform supports standard interfaces such as JDBC, ODBC, and REST APIs. TDengine IDMP can also connect to external databases, including MySQL, PostgreSQL, SQL Server, and InfluxDB 3, allowing organizations to work with data from existing systems without necessarily migrating it first. Combined with OpenAPI, SDKs, and MCP integration, this open architecture makes it easier to connect industrial data with third-party applications, analytics tools, and AI systems.

6. Developer-friendliness: AVEVA provides PI Web API and SDK-based development tools for integrating applications with PI System. TDengine offers REST APIs, SQL interfaces, and client libraries for a wide range of programming languages, including Python, R, Java, C#, Go, Rust, and more. This gives developers flexible options for building custom industrial applications and integrating TDengine into existing software environments. TDengine TSDB is available in an open-source edition, giving developers access to its database core. For organizations seeking a complete industrial data platform, TDengine All-in-One, including TDengine IDMP, is free forever for self-hosted deployments with up to 5,000 tags.

Migrating from PI System to TDengine

Replacing PI System does not have to mean a complete system cutover. TDengine provides a dedicated PI System connector that supports real-time data streaming and historical data backfill from PI Data Archive. It also supports mapping PI Points and PI AF Elements into TDengine’s time-series data models, helping organizations bring their existing industrial data into a modern platform.

Organizations can keep their existing PI System running while synchronizing data with TDengine, validating historical records, and testing new analytics workflows. This phased approach allows teams to evaluate TDengine without disrupting existing operations. Dashboards, calculations, and other application dependencies can then be assessed separately as part of the migration plan.

Learn more about the TDengine PI System Connector and explore the PI migration documentation.

Conclusion

PI System has played an important role in industrial data infrastructure for decades. However, as industrial organizations seek more flexible architectures and AI-driven capabilities, traditional historian functionality alone may no longer meet all their needs. TDengine offers a modern alternative that combines time-series data management, industrial asset modeling, real-time analytics, and built-in AI capabilities in one platform. With its PI System connector, organizations can also begin modernization alongside existing deployments instead of committing to a disruptive, all-at-once replacement.

Enterprises that want to make use of cutting-edge cloud and AI technologies with increased flexibility and reduced operational costs may consider TDengine as a solution for modernizing their industrial data stack. With its open ecosystem, TDengine delivers a wider range of integration and interconnection options than traditional industrial products, never locking you in to a single vendor or holding your data hostage. Efficiency-focused organizations and those interested in the Industrial IoT can benefit greatly from TDengine’s predictable and transparent pricing structure, significantly reducing data infrastructure TCO for deployments with large numbers of devices.

Full Feature Comparison