Example
Web Analytics with Open Source
How Cube and Retool work together
It’s never been easier to build internal tools and metrics dashboards powered by data from any data source. Cube sits between data and Retool to provide consistently defined and centrally governed data via REST, SQL, and GraphQL APIs—so you can focus on empowering your team, not wrangling your metrics.
Power your data applications with Retool 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.
Compatibility + Flexibility
Cube’s API-first approach and SQL-compliant protocol enable you to maintain every BI tool or data app with consistent metrics definitions, access control, and caching.
Integrate with anything
and anyone.
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.
Step-by-step guides on using Cube with Retool
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.
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
