Compare AVEVA Data Hub vs. TDengine

Chait Diwadkar
Chait Diwadkar
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With digital transformation accelerating across the industrial sector, enterprises need to choose the best products to modernize their data infrastructure. This article compares two of those products — TDengine and AVEVA Data Hub — to help you make informed decisions about your data management strategy.

About AVEVA Data Hub

Shortly after acquiring OSIsoft in 2020, AVEVA released its Data Hub product to facilitate sharing across PI System deployments. This cloud-based system removes many of the barriers to sharing data from disparate PI Servers, providing secure access to real-time data for users inside or outside of the company’s network. Bidirectional sharing is also available for a number of services within the AVEVA ecosystem.

About TDengine

TDengine’s focus on industrial data started in 2022 with the release of a connector for PI System, enabling users to replicate data from legacy data historians to TDengine’s open platform and benefit from its high-performance time-series database purpose-built for the Industrial IoT, as well as a range of third-party products in the TDengine ecosystem. Since that time, TDengine’s industrial capabilities have continued to grow, most notably with the addition of more industrial data sources and industry partners over the past two years.

Which Is Best for You?

AVEVA Data Hub and TDengine handle many of the same use cases, such as remote operations monitoring, real-time data for support personnel, data science analysis, and data sharing with external partners and applications. However, there are key differences between the products, which can be summarized as follows:

  1. Data centralization: Both products have strong support for cross-site data aggregation, including connectors for PI System, AVEVA Historian, OPC, and MQTT, ensuring that you can centralize your operations data in a single source of truth. Data Hub also enables ingestion from AVEVA Edge Data Store and Azure Event Hubs, while TDengine uniquely offers Kafka, InfluxDB, and OpenTSDB data sources.
  2. Data sharing: When it comes to distributing the data that you have centralized, both Data Hub and TDengine have rich capabilities as well, facilitating the sharing of data without requiring partners to have PI System or TDengine licenses. 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. Apart from views, TDengine also 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. This model is better suited for data-intensive AI and other real-time analytics applications than traditional view-based sharing.
  3. 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, Data Hub customers’ choices are much more limited in terms of system interoperability and expansion, with only a few vendor-provided offerings such as an integration with Power BI. TDengine, built on an open-source core, offers an open ecosystem with standardized interfaces such as JDBC and ODBC, facilitating integration with essentially any third-party product in addition to Power BI support.
  4. Product accessibility: Data Hub runs only in the cloud, specifically on Microsoft Azure, and requires users to have accounts in AVEVA Connect, while TDengine can be deployed on Amazon Web Services (AWS), Azure, or Google Cloud Platform (GCP) with no dependencies on any other products. Enterprises can get started in seconds with the fully managed TDengine Cloud offering, but TDengine also understands that not all industries and not all data are suited for cloud migration, and offers TDengine Enterprise as a self-hosted option for deployment on premises.
  5. Developer-friendliness: AVEVA provides a REST API through which applications can communicate with Data Hub, but other development options are limited. In addition to its own REST API, TDengine delivers a more developer-friendly experience with its client libraries for a wide range of programming languages — Python, R, Java, C#, Go, Rust, and more — including sample code that can be used in custom applications. And because TDengine’s core components are open-source software, developers have an even easier time diving into the code and designing their applications.
  6. Pricing model: Data Hub requires customers to purchase its Flex credits in order to use the service, which can result in dramatically increasing costs for enterprises with tens of thousands or millions of metrics to access. TDengine is designed as an affordable solution for big data, using a SaaS-like pricing model that ensures customers pay only for the resources that they use. Furthermore, its pricing is transparent, with TDengine Cloud prices even publicly available on the website.

Conclusion

For PI System and Wonderware customers that are happy with their current setup and want to stay within the AVEVA realm, especially those customers that are not price-sensitive or have few connected devices, AVEVA Data Hub is a great option for upgrading industrial data infrastructure. It is easy to set up the platform and stream your PI System data into Data Hub, removing barriers to data sharing and enabling data-driven services.

On the other hand, enterprises that want 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.

In addition, you can register for TDengine Cloud today and receive a free trial period of one month with no strings attached — no credit card information required and no gatekeeping by sales representatives. For on-premises PoCs, you can also download the free TDengine OSS and evaluate the product on your local system. With the future of industrial data quickly approaching and the benefits of Industry 4.0 and the IIoT waiting to be reaped, be sure that you’ve tried and compared a variety of systems to find the best solution for your organization.

  • Chait Diwadkar

    Chait Diwadkar is Director of Solution Engineering at TDengine. Prior to joining TDengine he was in the biotechnology industry in technical marketing, professional services, and product management roles and supported customers in pharma, medical devices and diagnostics on analytical chemistry, and genetic platforms.