how to choose the best data historian

For more than three decades, manufacturers have purchased data historians primarily to solve one problem: store time-series data from industrial systems. That is no longer enough.

In 2026, the historian sits at the center of a much larger conversation. Manufacturers are building architectures that must support AI initiatives, cloud strategies, digital twins, advanced analytics, enterprise integration, knowledge modeling, and operational intelligence programs that may not even exist yet. The challenge is that many organizations are still evaluating historians using criteria from 2006 rather than 2026. Questions about tag counts, compression rates, and database benchmarks still matter, but they are no longer the factors that determine whether a platform will support the next twenty years of growth.

The real question is this: Will the historian strengthen or constrain your future architecture?

When evaluating historian vendors today, these are the seven questions every manufacturer should be asking.

Most historian vendors claim to be "open." The problem is that openness has become one of the most abused terms in industrial software. A truly open historian should support standard industrial protocols, database technologies, APIs, security models, modern deployment options, and standardized data export methods.

More imporantly, your data should remain accessible without proprietary tools.

Ask vendors:

A useful litmus test is simple: If the vendor disappeared tomorrow, could you still access your data? If the answer is no, you are buying dependency, not infrastructure. More imporantly, your data should remain accessible without proprietary tools.

Many vendors now market themselves as "AI-ready." Very few explain what that actually means, or even know themselves. Cut through the marketing fluff quickly. AI systems require much more than historical process data. They require context, metadata, relationships, asset models, event data, and operational knowledge.

A historian that simply stores time stamped values may support reporting, but it may not adequately support future AI initiatives.

Ask vendors:

The next generation of manufacturing systems will not merely answer questions about values. They will answer questions about meaning. Your historian should help create that foundation.

Every vendor claims unlimited scalability. The term has become nearly meaningless without clarification. When discussing scalability, manufacturers should think across four dimensions.
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1. Data Volume: Can the platform handle billions of records?
2. Data Sources: Can it ingest hundreds or thousands of assets and facilities?
3. Users: Can engineers, operators, analysts, executives, and AI systems access data simultaneously
4. Architecture: Can deployments expand from a single site to an enterprise-wide footprint?

‍Ask vendors for real-world examples:

The goal is not to find the largest customer. The goal is to determine whether the platform can scale alongside your business for the next twenty years.

One of the biggest mistakes manufacturers make is assuming today's IT strategy will remain unchanged. It won't. Over the next decade, organizations will continue shifting between various architectures, including on-premise, private and public cloud, hybrid architectures, and edge computing. The historian you select today must support architectural flexibility tomorrow.

‍Ask vendors:

The right answer is not one deployment model. The right answer is optionality. Technology strategies evolve. Your historian should evolve with them.

Historically, historians focused on storing values. The next generation of industrial systems focuses on understanding assets, processes, equipment, products, and relationships. This introduces a critical question: Where does operational knowledge live?

‍Many organizations maintain critical information across Excel spreadsheets, asset frameworks, MES systems, ERP systems, tribal knowledge, and engineering documents.

Ask vendors:

Manufacturers increasingly recognize that data is only one part of the problem. Context is becoming equally valuable. The winners over the next decade will not be organizations with the most data. They will be organizations with the clearest understanding of what that data means.

Historian projects often last decades, technology vendors rarely do. As we have all seen over and over again, successful vendors get acquired, change direction, sunset products, or alter pricing models.

‍Ask difficult questions:

Architectural portability is frequently overlooked during procurement. It becomes critically important ten years later. The best architectures create freedom, the worst architectures create captivity.

You should never need permission from a vendor to access your own operational history.

This is arguably the most important question. Most historian evaluations focus on current requirements. The real value comes from future possibilities.

‍Ask vendors to explain how their platform supports:

Then ask a follow-up question:

What percentage of your R&D investment is focused on these areas?

‍A historian is not merely a storage system. It is a strategic architectural decision.The platform you select today may influence how your organization operates in 2035 and beyond so choose vendors that demonstrate a clear vision of where manufacturing technology is heading, not merely where it has been.

Everything you've just read influenced how we designed Timebase Historian. We didn't set out to build another historian that competed on compression algorithms, licensing models, or benchmark reports. We set out to build the historian we believe manufacturing needs for the next twenty years.

One that embraces open architectures instead of proprietary ecosystems. One that treats interoperability as a design principle rather than a marketing claim. One that exposes data through SQL, REST APIs, MCP, WebSockets, and industry standards like CESMII's i3X API so manufacturers can access their information using the tools they already know. One that runs wherever your architecture requires, whether that's on-premise, in the cloud, at the edge, or somewhere in between. One that was designed with AI in mind, giving intelligent systems direct, structured access to operational information instead of forcing them through layers of custom middleware.

And perhaps most importantly, one that removes cost as a barrier to building better manufacturing architectures.

Digital transformation is difficult enough. Manufacturers should be investing their budgets in creating operational value, not paying recurring licensing fees simply to retain access to their own historical data.

Timebase Historian is free because we believe the historian should become infrastructure. Like a database, a web server, or an operating system, it should be something manufacturers can confidently deploy as the foundation for everything that follows.

From there, organizations can focus on what truly creates competitive advantage: contextualizing information, building knowledge models, enabling AI, improving operations, and turning trusted data into better decisions.

If your digital transformation strategy begins with a historian, it should also begin with architectural freedom. That's exactly what Timebase Historian was built to provide.