A Sovereign Microsoft Fabric Alternative
Where Microsoft Fabric is Azure-only SaaS with per-dataset Power BI semantic models, Scrydon gives you a real, organisation-wide business ontology — sovereign, on open formats, and not locked to a single hyperscaler.
Real Organisation-Wide Ontology
One first-class business ontology across the organisation — not Power BI semantic models scoped per dataset.
Not Azure-SaaS-Locked
Runs inside your perimeter on open formats, European-native — not Azure-only SaaS on OneLake and the Microsoft ecosystem.
Grounded AI Built In
The same ontology grounds AI agents for accurate, explainable answers — beyond dashboards and Copilot over BI models.
Scrydon is a sovereign alternative to Microsoft Fabric: an ontology based data platform with a first-class, organisation-wide business ontology rather than per-dataset Power BI semantic models. Unlike Fabric, which is delivered as Azure-only SaaS on OneLake, Scrydon runs inside your own perimeter on open table formats, European-native, from air-gapped on-premises to cloud — so your semantics, data, and deployment are not tied to the Microsoft ecosystem.
Microsoft Fabric unifies analytics well for Microsoft-centric teams, but its semantics live in Power BI semantic models scoped per dataset, and the whole suite is Azure-only SaaS on OneLake. That ties your data, your modelling, and your residency to a single hyperscaler. Scrydon takes a different path: one first-class business ontology across the organisation, on open formats inside your own perimeter, European-native — so meaning is shared rather than fragmented per report, and sovereignty does not depend on Azure.
Microsoft Fabric Alternative in the Scrydon platform
One integrated, sovereign architecture. Here is where Microsoft Fabric Alternative sits — highlighted against the full stack it works with.
The AI OS for Humans & AI Agents to enable your processes
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Link your processes, knowledge & data to ontologies.
Unified storage, structured compute, and secure multi-modal data processing.
Autonomous operatives with specialised skills executing tasks across systems.
Sovereign pipelines, federated APIs, and seamless connector meshes.
Secure domain federation, trusted data sharing, and cross-boundary intelligence.
Microsoft Fabric Alternative in depth
Insights
Data sitting in warehouses and dashboards that nobody reads is data they can't use. The Insights layer changes that — giving the right people the right information without them having to ask for it. Every metric is anchored to the Cognitive Enterprise ontology, so a revenue figure doesn't arrive in isolation. Data in context — not just in dashboards.
Decision-makers get a live view of the enterprise — financial performance, operational health, procurement status — without waiting for a data team to prepare a report.
- Interactive notebooks: Python and SQL environments with full access to your lakehouse data — no data movement required.
- Visual dashboards: Pre-built, always-current reporting updated automatically as the business moves — no manual refresh, no stale numbers.
- Agent-native analytics: AI agents can query, summarise, and act on insights autonomously — closing the loop between analysis and action.
Cognitive Enterprise
Link your processes, knowledge & data to ontologies.
Most organisations have data they can't use — not because it doesn't exist, but because nothing connects it. The Cognitive Enterprise layer is the defining intelligence of the AI OS: a living, queryable semantic model of your organisation's entities, processes, and rules. It is the single source of truth that allows every agent, analyst, and workflow to reason about your business with a consistent understanding.
Without it, AI agents reason on noise. With it, they reason on the business.
- Entity graph: Model customers, accounts, orders, products, and any domain concept — then connect them with typed, traversable relationships.
- Process integration: Link real-world workflows to ontology entities so agents understand how data flows through your business.
- Continuous enrichment: Agents automatically enrich ontology nodes with fresh data from the lakehouse, keeping the model current without manual effort.
The Lakehouse is the high-performance data foundation underpinning the Cognitive Enterprise. It is built on StarRocks — a blazing-fast, vectorised MPP query engine delivering sub-second analytics, real-time updates, and high concurrency — and queries open Apache Iceberg tables directly, merging the flexibility of a data lake with the speed of a warehouse under a single, sovereign roof.
- Open Iceberg tables: Query Apache Iceberg and other open table formats directly — your data stays yours, with no proprietary lock-in and no data movement.
- Lightning OLAP: StarRocks' vectorised engine, cost-based optimiser, and materialised views power real-time SQL — from dashboards to agent reasoning — without data duplication.
- Integrated Vector Search: Store and query embeddings alongside traditional data, making the Lakehouse instantly ready for AI workloads.
Shared business meaning, not scattered semantic models
Fabric's semantics are Power BI semantic models defined per dataset, which fragments meaning across reports. Scrydon models the organisation once in a native ontology — entities, relationships, and definitions shared by every dashboard, report, and AI agent — and keeps it on open formats inside your own perimeter rather than in an Azure-only SaaS estate.
Organisation-wide ontology — Model meaning once across the whole organisation, not per dataset or per report.
Open, sovereign storage — Open table formats inside your perimeter — not locked to OneLake and the Microsoft ecosystem.
Consistent metrics — Each metric defined once so reports and agents reconcile, with no conflicting Power BI models.
Grounded AI — Agents reason over the ontology for explainable answers, beyond Copilot running over BI semantic models.
Sovereignty and shared meaning, not Azure lock-in
Fabric is a strong choice if you are all-in on Azure and Power BI — but that is exactly the constraint: Azure-only SaaS, OneLake storage, and semantics fragmented per dataset. A sovereign alternative gives you one organisation-wide ontology on open formats inside your own perimeter, European-native, with your keys — so your data, your modelling, and your residency are no longer tied to a single hyperscaler, and the same foundation grounds your AI.
Scrydon vs Microsoft Fabric
Both unify analytics. The difference is a real organisation-wide ontology versus per-dataset Power BI models — and sovereign, open deployment versus Azure-only SaaS.
| Capability | Scrydon | Microsoft Fabric |
|---|---|---|
| Primary focus | Ontology-based data unification and trusted insight | Unified SaaS analytics and BI |
| Semantic / ontology layer | Native, first-class organisation-wide business ontology | Power BI semantic models, scoped per dataset |
| Analytics & insights | Insights anchored to the ontology; consistent metrics everywhere | Deep BI through Power BI |
| Deployment & sovereignty | Sovereign — air-gapped to cloud, European-native, your keys | Azure cloud SaaS only |
| Openness & lock-in | Open formats, your perimeter, low lock-in | OneLake and the Microsoft ecosystem |
| Best fit | Organisations needing a sovereign semantic layer for insight and AI | Microsoft-centric BI teams |
Comparison is Scrydon's summary for orientation. Microsoft, Microsoft Fabric, Power BI, and Azure are trademarks of Microsoft Corporation; capabilities evolve — verify current details with the vendor.
Frequently asked questions
What is the best alternative to Microsoft Fabric?+
How is Scrydon different from Microsoft Fabric?+
Isn't a Power BI semantic model the same as an ontology?+
Is Scrydon more sovereign than Microsoft Fabric?+
Does Scrydon work with AI and Copilot-style assistants?+
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