Moving industrial time-series workloads to the cloud should make your data infrastructure easier to manage. But that depends on whether your database gives you the same product everywhere or adds another layer of complexity. This is where TDengine and AVEVA PI System take different paths.
One Unified Platform vs. Two Connected Systems
TDengine delivers a single, consistent experience whether you deploy on-premises or in the cloud. The same engine, SQL, and client libraries power all TDengine offerings regardless of location, and you can move workloads freely between edge and cloud deployments without rewriting code or changing tools.
PI System, by contrast, does not support cloud computing; customers that require cloud services must additionally purchase AVEVA CONNECT data services, a separate SaaS platform that runs exclusively on Microsoft Azure. To send data there, you also need a PI-to-CONNECT agent that publishes data from your on-premises PI Server to the cloud service. In practice, that means operating and securing two platforms: your local historian and the cloud data service.
Cloud Deployment Comparison
| TDengine | PI System + AVEVA Connect | |
|---|---|---|
| Platform | On-prem: Windows or Linux Cloud: AWS, Azure, or GCP | On-prem: Windows only Cloud: Azure only |
| Engine | Same core engine everywhere | Separate cloud service (AVEVA CONNECT) |
| Data Movement | Direct access; no extra broker or agent | Requires data-transfer agent |
| App Compatibility | Identical SQL, APIs, and clients | Different models for PI System and AVEVA CONNECT |
| Operational Scope | One platform to deploy / monitor | Two platforms + integration layer |
Edge–Cloud Synchronization
TDengine is built for seamless edge–cloud synchronization, giving enterprises the flexibility to deploy nodes at each site while also maintaining a centralized cloud platform where data from all sites is consolidated. At the edge, TDengine handles real-time data ingestion, buffering, and analytics, and in the event of an outage, edge nodes continue to operate, ensuring no data is lost. Once the connection is restored, TDengine automatically backfills historical data to the cloud or central server. For enterprises that are fully on-premises, this architecture can also be used for synchronizing edge nodes to a data center or corporate office instead of the cloud.
All TDengine instances, whether at the edge or in the cloud, share a consistent schema, asset framework, and metadata model. That means data from different facilities, lines, or regions can be analyzed together with zero transformation or reconfiguration. Enterprises gain a single, coherent view of operational data across every site, while still maintaining the ability to act locally on the edge for latency-sensitive or safety-critical use cases.
In contrast, PI System’s hybrid cloud strategy depends on external components such as PI-to-CONNECT agents and AVEVA CONNECT data services to bridge on-premises and cloud environments. This approach provides connectivity but not true synchronization: data must be published, replicated, or reformatted before it can be used in the cloud. As a result, real-time visibility and unified data modeling across sites are harder to achieve, and maintaining consistency between local and cloud systems requires additional configuration and operational effort.
Why the Difference Matters
With TDengine, you can run the same software at the edge, in the cloud, or both, and never experience compatibility issues or struggle with different interfaces. A single set of tools covers data ingestion and processing as well as system monitoring, backup, and security. And TDengine’s continuous, automated synchronization eliminates the need for custom scripts or third-party replication software.
Additionally, TDengine supports AWS, Azure, and GCP, so enterprises with existing cloud operations can select the service provider they prefer. Organizations that want to offload administrative work can select our fully managed TDengine Cloud, while those looking for more control can deploy self-hosted TDengine on their cloud servers.
By contrast, PI System’s cloud path through Azure-only AVEVA CONNECT adds another SaaS environment to configure, monitor, and budget for. In practice, this extra layer makes it harder to maintain a seamless experience across the entire data lifecycle, and already overburdened IT teams end up managing two distinct systems instead of one unified platform.
Final Take
If your cloud strategy is about portability and operational simplicity, TDengine offers a true “run-anywhere” model: one engine, one experience, on-premises or in the cloud.
PI System’s approach provides cloud connectivity, but at the cost of managing two distinct layers: the on-premises historian and the CONNECT Data Services platform. For many teams, that’s one platform too many.
