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Building dashboards over a semantic layer with Superset and Cube
Build a Superset Semantic Layer with Cube.
How Cube and Superset work together
Cube sits between your data source and Superset, providing consumers with consistently defined, secure, and performant data. By managing data modeling, access control, and caching upstream, you can be sure every data consumer in your org using Superset—and every other data app—will be working with the same fast data protected by the same permissions.
Power your data applications with Superset and Cube
Headless = Customized
Decoupling BI from your front-end means orchestrating data modeling, access control, and caching once—while building presentation layers for any use case.
Easily tailor your
user experience.
Performance + Reliability
Redundantly and directly querying your data source results in latency and unnecessary costs. Cube’s caching layer, pre-aggregations, and query queuing fix that.
Skip latency;
expect speed.
Security + Governance
Reconfiguring data access control for every data app in your stack opens the door to inconsistencies and gaps. Centralize permissions upstream for uniform security.
Maintain ubiquitious
access control.
Additional information on using Cube with Superset
With Cube, we’ve been able to speed up time to release a new data model to production by 5x and decrease analytics downtime by 90%.
Alessandro Lollo
Senior Data Engineer at Cloud Academy
We can develop and ship analytics products without dealing with any net new infrastructure development going forward. Our efforts are focused on what matters: the data and the UI. Read the Case Study
Louis Zuckerman
Sr. Staff Software Engineer at Simon Data
Cube really stood out as a great fit for our use case. We were able to level‑up our data infrastructure without needing to build a full‑blown and expensive data pipeline. Read the Case Study
Jc Weinrich
Architect in Jobber
Interest piqued? Try Cube's semantic layer.
Fully managed hosting of your Cube apps
