Skip to main content

CryspIQ® vs Microsoft Fabric

These two answer different questions.

  • Microsoft Fabric asks: "Where do I store and process all my data, at scale?"
  • CryspIQ® asks: "Can I trust the answer?"

CryspIQ® supplies what Microsoft Fabric expects you to build, rather than replacing Fabric. Fabric is a unified SaaS analytics platform: OneLake for storage, Data Factory for ingestion, data engineering and warehousing, Real-Time Intelligence, data science, Power BI and Fabric IQ, on one capacity and one bill. CryspIQ® is the enterprise model those workloads are meant to be pointed at. The question is not which to buy — it is where business meaning gets attached, and how many times.

Is CryspIQ® an alternative to Microsoft Fabric?​

No. CryspIQ® doesn't replace OneLake, Data Factory, Fabric's compute, Power BI or Copilot, and it can read from the bronze or silver layer you already land in OneLake. What it adds is the governed enterprise model: business definitions, master data and data quality, attached to the data as it loads, so every report, data agent and Copilot answer gets the same answer.

A note on the name​

Microsoft Fabric is a product. A data fabric is an architectural pattern, and the phrase predates the product by years — it is a G2 software category with more than eighty listings in it.

CryspIQ® is listed in that category, and the pattern describes it: one governed model over data from many sources, independent of where each source came from. It is not a claim to be Microsoft Fabric, or an alternative to it — and CryspIQ®'s own description deliberately avoids the phrase, because a term Microsoft ships a product under is the wrong place to spend a first sentence. Both things being called fabric is unhelpful, and worth saying plainly rather than leaving a reader to work out.

What Fabric gives you​

A genuinely unified estate. One tenant-wide lake in OneLake with a single physical copy and shortcuts instead of duplicates, ingestion and orchestration, warehouse and lakehouse compute over the same Delta tables, real-time streams, notebooks, and Power BI sitting directly on top through Direct Lake. Purview adds cataloguing and lineage across Fabric and beyond it, and everything inherits Entra identity.

For an organisation already committed to Microsoft, the integration is the product, and CryspIQ® works alongside infrastructure like this rather than reproducing it.

Where Fabric puts meaning​

In three places, which is the part worth examining.

The gold layer. Fabric's recommended pattern is medallion: bronze as landed, silver cleaned and conformed, gold business-ready for a particular audience. Meaning accumulates in the pipeline rather than in the data, so it is applied per gold table, by whichever team built it.

Power BI semantic models. These are Fabric's answer to business definitions, and a good one — measures and relationships defined once and inherited by every report that connects through the model.

Fabric IQ ontologies. Fabric IQ, generally available since Microsoft Build 2026, adds an ontology item (still in preview at the time of review) that describes business entities and their relationships and binds them to tables in OneLake. Data agents, Copilot and other AI tools can then reason in business terms rather than over raw tables. It is Microsoft's clearest move yet towards the idea CryspIQ® is built on, and it is worth taking seriously.

The difficulty is that these are several answers to the same question, each built and maintained by your team, and none is authoritative over the others. A measure defined in a semantic model governs the reports using that model. A notebook, an ML job, a Real-Time Intelligence query or a second workspace's model reading the same Delta tables in OneLake gets the tables, not the measure — and defines revenue again, its own way.

An ontology narrows that gap for the AI tools that use it, and it works the way a semantic layer does. You design the entities, and they are bound over tables still in the shape the source systems produced them. It says what a customer is. It doesn't check whether the customer records are complete, and it doesn't make five records for one customer into one. See CryspIQ® vs a semantic layer.

OneLake solves the copy problem, not the meaning problem. One physical copy of the data is a real advance over the several most organisations hold. It says nothing about how many definitions of customer sit on top of that single copy, and in practice the number rises with each workspace.

What CryspIQ® changes​

CryspIQ® attaches meaning at entry. The fact type carries the business definition and the security classification, and quality is measured as data loads. Once meaning is a property of the stored data, the layers whose job was to add it later have nothing left to do — and there is no bypass route, because a consumer reading the data reads the definitions with it.

On FabricWith CryspIQ®
Where business meaning livesGold tables, Power BI semantic models and Fabric IQ ontologies, applied over source-shaped tablesOn the fact type, stored with the data, once
Consumers outside the semantic model or ontologyGet Delta tables and their own interpretationInherit the same definitions
Enterprise ontologyYou design it, entity by entityThe model's parties, places, fact types and dimensions, ready on day one
Enterprise data modelYou design and build itPre-defined, patented, ready on day one
Master dataYour approach to maintainA single instance per party, enforced structurally
Data qualityRules you write and maintain per pipeline or tableAssessed as data loads against the model, scored organisation-wide
LineageReconstructed via Purview and pipeline metadataAutomatic, through the link key
A new business questionUsually needs a gold table or model change firstNo modelling step between question and answer

Where Fabric is stronger​

Everything CryspIQ® does not attempt, and the list is long: real-time streaming analytics, data science and model training, unstructured data at volume, arbitrary transformation, and exploratory work where the shape of the answer is not known in advance.

It is also far less invasive. Fabric requires no mapping exercise — you point it at your sources and you are running. And if your organisation lives in Power BI and Microsoft 365 already, the adoption cost for report consumers is close to zero, which is a real advantage and should not be talked past. The same goes for AI: Fabric IQ connects business meaning directly to Copilot, data agents and Copilot Studio, inside tools your people already use.

There is a genuine trade in flexibility too. Fabric will model anything you can write code for. CryspIQ® asks your data to fit seven fact types and a fixed set of dimensions — fixed at the level where organisations are alike, open at the level where they differ.

How they fit together​

CryspIQ® runs on its own Azure SQL Database, not in Fabric, and its connectors normally map business-relevant data directly from source systems. Where data is already landing in OneLake, CryspIQ® can map from the bronze or silver layer instead, into standardised business entities, independent of how each source produced them. Fabric keeps ingesting, keeps serving real-time and data science workloads, and keeps Power BI as the presentation surface.

The useful arrangement is usually that Power BI semantic models stop being the place definitions are decided and become the place they are presented — sourced from one governed model instead of maintained per workspace. Where a semantic model is already embedded in hundreds of reports, that is the sensible order of events. See CryspIQ® vs a semantic layer for the underlying distinction, and co-existence for how adoption sequences without a migration.

Microsoft Fabric product details last reviewed October 2026.