PI System comparison
PI System alternative: TDengine Historian
TDengine Historian does the PI work most plants actually need — tag storage, asset context, dashboards and reporting — in one platform, with SQL access built in. We run a comparison on your tag list and quote what it would cost to run — no blanket savings claim until we have your numbers.
What is TDengine Historian, and how does it compare to PI System?
TDengine Historian is a modern industrial historian: a purpose-built time-series database plus an industrial data layer for assets, dashboards and analysis. If your team knows PI, the jobs are familiar — keep years of tags, put them in equipment context, trend them, report on them — without buying PI Vision, PI DataLink or PI Integrator as separate products.
SQL is built in. Visualisation is built in. Excel workflows are built in. That is why sites looking at PI cost and at industrial AI land on the same platform: the data is already where analysis and language models can use it.
What covers each part of PI
Here is how the PI stack maps onto TDengine Historian. It is one product covering the jobs below — but AF models, Vision displays and DataLink workbooks are rebuilt in IDMP, not copied. We walk your screens, Excel reports and event logic in a proof of concept so you see parity on your plant, not only on a diagram.
| PI System area | TDengine Historian coverage |
|---|---|
| PI Data Archive / PI Server | Industrial time-series storage |
| PI Asset Framework | Asset hierarchy, templates and attributes rebuilt in IDMP from the AF inventory — ingest maps PI Points or AF elements into TDengine tables rather than copying AF across |
| PI Vision / ProcessBook | Dashboards, trends, Canvas, and process visualization |
| PI DataLink | Excel access, exports, and reporting workflows |
| PI Analyses / Event Frames | Calculations, events, alerts, and event history |
| PI Interfaces / Connectors | OPC UA, OPC DA, MQTT, PI connector, files, APIs |
| PI Buffering / HA | Local caching, store-and-forward, and cluster high availability |
| PI Integrator / APIs | JDBC, ODBC, REST API, BI, and enterprise integration |
What we prove in a PI comparison PoC
- We map your PI system onto one platform. Storage, asset models, dashboards, Excel access and APIs are in the historian platform — asset models and panels still need engineering on your plant.
- We show your reports coming out in SQL. We take the DataLink workbooks your team depends on and reproduce the numbers by querying the historian directly, instead of through a proprietary client.
- We prove the move needs no weekend cutover. We stream live data into TDengine while PI stays up, backfill history in batches, and rebuild the Vision screens and event frames operations rely on, so applications only cut over once the numbers match.
- We prove the groundwork industrial AI needs. The same platform can hold an asset model and your manuals — once we model assets, load documents, and connect a language model — so analysis can run against data that stays on site.
Frequently asked questions
Is TDengine a full PI System replacement?
The core historian jobs — tag storage, asset models, dashboards, Excel reporting, events, connectors and open APIs — live in one TDengine Historian platform instead of a core server plus paid add-ons, but every PI installation is different. AF models, Vision displays, DataLink workbooks, event frames and custom integrations have to be rebuilt and proven on your own tags before anyone calls it a full replacement.
Do we have to rip out PI in one cutover?
No. TDengine is designed to run beside PI. New values stream in while PI stays live; history is backfilled in batches; applications move only when the numbers match. You keep a rollback path the whole way.
Why are African sites looking at TDengine?
They still need a serious historian — long retention, asset context, dashboards their teams will use — without stacking extra licences for visualisation and Excel. TDengine’s published model prices by tag count and includes dashboards and Excel access in the historian, so many sites avoid separate PI Vision and DataLink seat costs. We confirm current licensing against your tag inventory in discovery, and every PI installation still needs a proof of concept on its AF and reports. SQL is built in, and industrial AI can run against data that stays on site.
How does TDengine IDMP compare to PI Asset Framework?
IDMP covers the same job as Asset Framework plus PI Vision — equipment templates, attributes, hierarchies and operator displays — once we rebuild them from your plant. There is no AF import: we inventory the AF structure and rebuild the templates, attributes and panels your team actually uses. It then goes further. You attach manuals, SOPs and P&IDs to those assets and IDMP indexes them, so an AI assistant can retrieve them — but only after the documents are loaded and a language model you control is connected, which can run on your own network. AF models the plant well; IDMP is built so the plant can also be queried in language.
Run the comparison on your own tag list
Share a tag list and the screens and Excel reports your team depends on. We map what TDengine covers, what it would cost to run, and where PI is still the right answer.