timbr core
Caching Engine
Timbr’s Caching Engine is a multi-tiered capability that boosts query speed and lowers compute costs by intelligently caching semantic mappings and aggregates, delivering high-performance, secure analytics across large, distributed datasets without sacrificing semantic accuracy.
Four-Tier Semantic Cache
Timbr’s caching engine supports four distinct tiers, each optimized for a different cost-performance balance:
Tier 1:
Local Database Materialization
Materialize data directly in the source database, ideal for tight integration and fast pushdown.
Tier 2:
Data Lake
Storage
Cache results in cost-effective object storage for large datasets with less stringent latency needs.
Tier 3:
SSD
Storage
Store materializations in high-speed SSD layers within the Timbr cluster to optimize frequent access.
Tier 4:
In-Memory
Cache
Persist selected views in memory for ultra-fast, real-time dashboards, and high-frequency queries.
Each tier supports full and incremental materialization, and cached data can be promoted or demoted between tiers to align with workload patterns and cost-performance goals.
Governed, Secure, and Compliant
Cached data is subject to the same governance as live data:
· Role-based and row-level access policies are applied uniformly.
· Column masking and concept-level restrictions remain enforced.
· Audit trails log cache usage and refresh activity.
· Refresh logic is fully visible and customizable per dataset.
These controls make the caching engine suitable for multi-tenant environments and regulated industries.
Performance at Scale
Whether you’re powering a dashboard, reducing load on compute warehouses, or delivering sub-second responses to AI systems, Timbr’s caching engine helps you scale without moving data.
· Guided cache tier selection based on usage patterns and performance goals.
· Partitioned caching for time-based or category-based splits.
· Materialization of both mappings and ontology views in SQL.
· Defined entirely in SQL, ensuring compatibility with native data infrastructure.
Benefits at a Glance
The Caching Engine is a core part of Timbr’s performance strategy, powering semantic intelligence at speed and scale.
Four-tier strategy balances speed, storage, and cost
Automatically reuses and refreshes semantic projections
Maintains governance and access control at every layer
Semantic awareness ensures cache correctness
High-performance workloads without moving data
Smart Materialization and Projection Reuse
- Semantic Projections: Timbr automatically generates pre-aggregated tables based on usage patterns or defined cache indexes.
- Reusable Results: Cached aggregates are reused across compatible queries to minimize compute costs.
- Hybrid Live-and-Cached Querying: Mix live and cached data dynamically based on semantic context and freshness policies.
- Manual or Automated Refresh: Refresh caches via scheduler, SQL command, or external API, supporting incremental or full refresh based on partition or timestamp logic.
Semantic-Aware Optimization
Unlike generic caching layers, Timbr’s engine is fully aware of semantic context, including:
- Ontology structure, relationships, and hierarchies.
- Accurate cache invalidation to ensure correctness on data changes.
- Safe reuse prevention for incompatible queries.
- Preservation of row-level security and masking in all cache tiers.
This semantic awareness guarantees that cached data remains trustworthy and compliant, no matter the access point.
