timbr core
Data Virtualization
Timbr’s Data Virtualization engine integrates access to distributed sources via a unified ontology-based semantic model, eliminating replication and ETLs while delivering SQL queries with full semantic context across databases, cloud warehouses, data lakes, and APIs.
ZERO Data Movement
Timbr virtualizes access to relational databases, cloud warehouses, data lakes, NoSQL systems, and APIs, allowing users to:
- Query multiple sources as a single unified model.
- Avoid physical movement, duplication, or materialization of data.
- Maintain live access to the freshest data, governed by the semantic layer.
- Use standard SQL to interact with complex, federated environments.
No matter where your data lives, Timbr exposes it through the ontology-based model that makes distributed querying intuitive and efficient.
Federated Query Execution
When a query spans multiple sources, Timbr’s virtualization engine dynamically federates across systems:
- Executes distributed joins, unions, filters, and aggregations in parallel.
- Uses semantic query planning to identify only the relevant data from each source.
- Pushes down predicates and operations to underlying systems in their native dialects.
- Optimizes query paths for minimal latency and cost.
Federated computation happens only when needed, ensuring that local queries remain fast and efficient.
Engine-Agnostic and Extensible
- Relational: Databricks, Snowflake, Synapse, BigQuery, PostgreSQL, MySQL, Oracle, etc.
- Data Lakes: Delta Lake, Iceberg, Parquet over S3/ADLS/GCS.
- NoSQL: MongoDB, Elasticsearch.
- APIs: REST, OData, OpenAPI-based endpoints.
- Virtualization Layers: Integrates with Presto, Trino, or Databricks SQL if already in use.
SQL Dialect Translation
and Pushdown Optimization
Timbr speaks the SQL variant of each connected data source:
local query translation
Translates logical queries from the semantic model into native SQL for each engine.
cross-dialect translation
Supports cross-dialect translation, so users query in standard SQL, regardless of backend.
pushed-down compute
Pushes down filters, joins, groupings, limits, and calculations.
Minimal data transfer
Minimizes data transfer between sources and avoids expensive reshuffling.
The result: performance that scales with your infrastructure, without sacrificing abstraction or ease of use.
Governance Without Friction
All virtualized queries pass through Timbr’s governance layer:
- Row- and column-level security.
- Data masking and policy enforcement.
- Semantic context enforcement for accurate and authorized querying.
- Audit logging and lineage for full traceability—even across sources.
This allows you to offer governed self-service access to data, even when scattered across dozens of systems.
