Solution
Blazing Fast Analytics with Optimized Queries, Measures in SQL and Smart Caching
Timbr dramatically improves query performance across your data platforms by optimizing SQL, translating modeling logic into efficient database-native expressions, and leveraging smart caching.
Get the speed you need without sacrificing governance or interoperability.
How Timbr Accelerates Dashboard Performance at Any Scale
Native Pushdown
to Any SQL Engine
Timbr compiles semantic models into highly optimized, platform-native SQL, leveraging the full processing power of engines like Databricks Photon, Snowflake’s MPP, and BigQuery’s columnar execution. No platform-specific tuning required.
SQL Measures
Optimized for Execution
Timbr’s SQL measures are deeply aware of data structures. They encode relationships, filters, and hierarchies directly into reusable logic, resulting in dramatically faster aggregations and drilldowns, even over complex schemas.
Four-Tier Caching
Built for Real Workloads
With Timbr’s caching framework, queries are served from the fastest layer available, dramatically reducing query costs, network overhead, and compute usage, especially in high-concurrency environments.
Smart Query
Rewriting
Timbr’s query engine inspects each query and dynamically rewrites it into an optimal execution plan. This eliminates redundant operations, applies filters early, and avoids costly Cartesian joins, improving both speed and cost-efficiency.
No Logic Duplication,
No Pipeline Overhead
All business logic: metrics, joins, constraints, transformations, lives in the semantic layer. This eliminates the need for logic duplication across tools and allows for fast iteration and consistent performance without data movement.
