How dhino compares
dhino is a governed access layer, not a data platform or a query generator. Here is how it differs from the tools it gets compared to, and where it fits alongside Microsoft Fabric.
The short answer
Every request to dhino runs a pre-defined template with deterministic execution. The same question returns the same answer, for every consumer, with field-level access and audit trails built in. That is the core difference.
dhino vs text-to-SQL
Text-to-SQL generates a query at runtime and hopes it is right. dhino runs pre-defined templates. That distinction decides everything else.
| Text-to-SQL | dhino |
|---|---|
| Generates a SQL query at runtime from natural language | Executes a pre-defined template with parameterized logic |
| Accuracy degrades on complex schemas; results can vary each time | Same question, same answer, every time. Deterministic. |
| Governance is applied at the query level, often as a prompt | Field-level access, role-based permissions, and audit trails built in |
| Primarily a tool for developers and analysts | One layer for business users, applications, and AI agents |
| Good for ad-hoc exploration | Built for production data access |
dhino vs a semantic layer
A semantic layer describes how to query the data. dhino executes against the data. They overlap on modeling; they diverge on execution.
| Semantic layer | dhino |
|---|---|
| Describes the data: entities, metrics, joins | Executes against the data through parameterized templates |
| Still relies on generated queries underneath | No runtime generation. Templates are tested and fixed. |
| Better UX than raw SQL, same execution risk | No execution risk. Same template, same result. |
| Typically consumed by BI tools | Consumed by humans, applications, and AI agents through one layer |
dhino and Microsoft Fabric
Fabric is a data platform: lakehouse, compute, BI. It is Microsoft's answer to Databricks and Snowflake. dhino is a governed access layer that sits on top of whatever data you have, Fabric included.
Fabric is where data lives. dhino is how it gets served to the people, applications, and AI agents that need it. A Fabric customer is typically a strong fit for dhino: Fabric gives them the data, dhino gives every consumer a governed path to it.
The categories dhino actually displaces: text-to-SQL tools, hand-rolled semantic layers, and the "every team builds its own governed API" pattern.
Talk to us about where dhino fits
Every data environment is different. Tell us what you are running and we will tell you honestly where dhino fits and where it does not.