Modernize Your Wonderware Sites with TDengine

Jeff Tao
Jeff Tao
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When it comes to stability, Wonderware Historian (now known as AVEVA Historian) has been the name of the game for decades. It’s built on a rock-solid foundation that ensures essential data is never lost and unplanned outages don’t occur — in the event of an incident, the system can fail over to a standby node in only 1 second. Wonderware customers know that they can depend on its data historian to form the core of their industrial data infrastructure and have relied on it for years.

That said, the requirements of today’s industrial applications are more data-intensive than ever before — modern analytics applications query larger data sets and require lower latency than were imaginable when Wonderware was originally designed — and unfortunately Wonderware’s performance just isn’t up to the task. Performance-heavy queries return results slowly, and sometimes time out without returning anything at all. And although Wonderware’s visualization tools are a great fit for their customers’ use cases, it’s not possible to get a global view of multiple Wonderware Historian sites, meaning that data can easily become siloed.

With our new Wonderware connector, TDengine is providing a path forward for customers who want to continue benefiting from the legendary stability of Wonderware while overcoming its performance limitations and centralizing data from multiple sites into a single source of truth. By deploying TDengine on top of Wonderware Historian, you can replicate historical and live data from all your Wonderware sites into a single TDengine instance, deployed in the cloud or on-prem in your data center. You can then run queries in TDengine’s high-performance cloud-native time-series database, ensuring blazing fast response times even with petabytes of data generated per day. And because TDengine supports standard SQL, Wonderware operators can get started easily and make use of their existing knowledge without lengthy retraining.

What’s more, thanks to TDengine’s open ecosystem, you can integrate your favorite third-party components into your infrastructure to perform analytics, create dashboards, and generate reports based on cross-site data centralized within TDengine. TDengine’s range of industrial data connectors also enable you to centralize Wonderware Historian data along with data from other sites running PI System, OPC, MQTT, and more.

  • Jeff Tao
    Jeff Tao

    With over three decades of hands-on experience in software development, Jeff has had the privilege of spearheading numerous ventures and initiatives in the tech realm. His passion for open source, technology, and innovation has been the driving force behind his journey.

    As one of the core developers of TDengine, he is deeply committed to pushing the boundaries of time series data platforms. His mission is crystal clear: to architect a high performance, scalable solution in this space and make it accessible, valuable and affordable for everyone, from individual developers and startups to industry giants.