One platform to federate, model & govern your data
SemanticFed brings a federated query engine, a typed semantic layer, and governance at the query edge into a single control plane — so every team reaches every source through one consistent, governed interface.
Query across every source as if it were one
A distributed query engine that plans, optimizes, and executes across all your sources — pushing work to where the data lives.
Federated SQL
Write one ANSI-style SQL statement that joins tables across databases, warehouses, lakes, and APIs. The engine resolves it across sources and returns a single result.
Cost-aware planner
Predicates, projections, and aggregations are pushed down to each source, and the planner estimates cost to choose the path that moves the fewest bytes.
Virtual views
Model the shape you need as a view over federated sources. Transformations and joins run at query time — no materialized copy to operate.
Caching & materialization
Opt in to result caching or materialization on the hot paths that need millisecond latency, with a freshness policy you control. Everything else stays live.
Model your business once, consume it everywhere
A typed semantic layer above your sources so entities, dimensions, and metrics are defined in one governed place.
Entities, dimensions & metrics
Define “active revenue” or “net retention” once as a documented, typed object. Every consumer resolves the same definition, so the numbers agree by construction.
Data catalog
A searchable catalog of governed datasets with descriptions, types, and lineage, so analysts find and understand data instead of guessing at schemas.
Typed model
Types and relationships flow through the model, so a downstream tool — or an AI agent — knows what a field means and how entities connect.
Versioned definitions
Semantic definitions live as code you can review and version, so a metric change is a reviewable, traceable event, not a silent dashboard edit.
Govern access in one place, enforce it everywhere
Policy, masking, lineage, and audit applied at the federation edge — consistent across every source and tenant.
Row & column policy
Row filters and column masking defined once and enforced on every federated query, no matter which underlying system holds the data.
Audit trail
Every query is attributable to an actor and logged with the policy that applied — so access reviews read as one consistent audit log.
End-to-end lineage
Every dataset traces back through its virtual views to the physical sources, so you can always answer where a number came from.
Inherited identity & RBAC
Authentication and RBAC are inherited from the Burdenoff platform and enforced at the edge — SemanticFed never reinvents auth.
Trustworthy context and a single endpoint
Serve the whole governed model to humans, tools, and AI agents through one consistent interface.
Governed AI context
Point agents and copilots at the semantic layer so they reason over documented metrics with access policy applied — grounded answers, not hallucinated schemas.
SQL & GraphQL endpoints
Expose the entire federated model through one SQL interface and a GraphQL API, so apps and tools integrate against a stable contract, not source drivers.
Connector library
Register relational databases, cloud warehouses, object-storage lakes, and SaaS REST/GraphQL APIs. Each connector handles auth, introspection, and push-down.
Query observability
Per-query plans plus latency, push-down, and source-health metrics, so you can operate the query layer with confidence instead of guesswork.
Connect anything
Databases, cloud warehouses, object-storage lakes, and SaaS APIs all register as federated sources behind one query interface.
Why federate?
How data federation compares to copying data into yet another store.
| Capability | SemanticFed | Hand-built ETL | Single warehouse |
|---|---|---|---|
| Query data in place (no copy) | Roadmap | — | — |
| One governed semantic layer | Partial | — | Partial |
| Policy enforced across all sources | Partial | Partial | Per-warehouse |
| Live results from operational systems | Roadmap | — | — |
| End-to-end lineage & audit | Partial | Partial | Partial |
| Governed context for AI | Partial | — | — |
See it on your own data
SemanticFed launches in 2026. Join the waitlist or talk to us about your sources and the questions you want to answer across them.