Ensure your Databricks investment pays off across every team, tool, and AI agent

Cube and Databricks work in tandem to provide consistent, governed, and high-performance data across every dashboard, spreadsheet, and AI agent. Begin using Cube, the universal semantic layer for Databricks, in minutes. Simply sign up, connect Databricks, generate models, and publish consistent metrics for any data consumer.

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Increase Operational Efficiency:
Support modern OLAP and AI workloads simultaneously.
Centralized Governance:
Define metrics once and reuse them across tools.
Enhanced Performance:
Speed up dashboards and multidimensional queries.

Make Your Databricks Data AI- and BI-Ready

While Databricks handles your data storage and compute, inconsistent metrics often arise because teams create their own definitions in BI tools and spreadsheets. Cube resolves this by sitting between Databricks and all data consumers, providing an AI- and BI-ready single source of truth. Your data warehouse is ready, but are your metrics?

This was an exciting journey with a great deal of changes in the technologies. What we started with, we no longer use. The landscape has changed but right now I feel we are in the right place with the right technologies and right partner in Cube.

Fortune 500 Manufacturing CompanyRead the Case Study

I see Cube as a key technology in our data stack because it serves a very real purpose in adding semantics, speed, and security administration at the API layer. It's something that you don't want to build yourself. I can see us using Cube much more in the future.

Anonymous CompanyRead the Case Study

Deliver your Databricks data wherever it’s needed

Power all your downstream data consumers with consistent Databricks data, avoiding metric sprawl. Combine Cube and Databricks to expose data via SQL for BI tools, REST and GraphQL for embedded analytics, MDX for Excel, and DAX for Power BI. This ensures that AI agents, BI dashboards, spreadsheets, and embedded analytics all access the same logic without the need for rebuilding in each tool.

Secure your Databricks data at the semantic layer

Set row-level, column-level, and user-level policies upstream from data consumers to ensure automatic application across all tools and APIs. This allows your governance policies to follow your data, even into AI and spreadsheets, supporting tool preference while maintaining compliance.

Optimize Databricks performance and reduce compute costs

Integrate Cube with Databricks to leverage its robust caching and sophisticated pre-aggregations, significantly boosting query performance while lowering warehouse strain and expenditure. Cube’s caching enhances every data connection, ensuring sub-second API response times even during peak concurrency.

Ground AI agents on trusted context from Cube

Cube D3’s AI Data Engineer and AI Data Analyst agents integrate seamlessly with Databricks. Databricks serves as the data source, while Cube provides deep context from the semantic layer. This integration automates insights, clarifies outputs, and ensures compliance with governance protocols.