reference architecture
Databricks Lakehouse and Timbr:
Streamlining Real-Time Data Workflows
Databricks Lakehouse combines data engineering, analytics, and AI/ML workflows into a single platform.
By embedding Timbr, enterprises can unlock a semantic layer that simplifies exploration, enhances collaboration, and connects data across raw, restricted, and gold zones.
Why Timbr with Databricks Lakehouse ?
Timbr democratizes the power of the Databricks Lakehouse by creating a seamless, connected data environment, enabling businesses to simplify workflows and unlock actionable insights.
How Timbr Embeds into the Databricks Lakehouse
Timbr is embedded as a semantic layer within the Databricks Lakehouse, transforming data by:
- Unified Semantic Graph: Represent Databricks data zones as a single semantic graph, making complex relationships easier to query with SQL.
- Integration with Unity Catalog: Seamlessly define and manage semantic models within Databricks workflows, leveraging Unity Catalog for centralized governance.
- Enhanced Querying: Simplify SQL queries by replacing JOINs with semantic relationships across Delta Lake and real-time data pipelines.
Features in Action
- Real-Time Processing: Combine Timbr’s semantic capabilities with Delta Live Tables for enriched real-time analytics.
- Transitive Reasoning: Automatically propagate shared properties across datasets, reducing redundancy and ensuring consistency.
- Metrics Management: Define, manage, and analyze metrics within the Lakehouse using Timbr’s Metric Store, accessible via SQL and BI tools.
Impact
By integrating Timbr, enterprises can:
- Simplify Workflows: Streamline data pipelines and queries with reusable semantic relationships.
- Foster Collaboration: Align teams around shared semantic models, improving decision-making.
- Enable Scalable Analytics: Leverage Databricks’ scalability with Timbr’s semantic intelligence for advanced analytics.
