Cube + Preset
Build consistent, governed analytics with Cube's semantic layer and Preset's visualization platform. Define metrics once, use everywhere, and ensure everyone trusts the numbers.
Semantic layer meets open analytics
Consistent metrics everywhere
Define business logic once in Cube's data model. Every Preset dashboard uses the same metric definitions—no more conflicting numbers.
Pre-aggregation for speed
Cube pre-computes common aggregations so dashboards load instantly. Query billions of rows without waiting or straining your warehouse.
Access control built-in
Cube's row-level security flows through to Preset. Users only see the data they're authorized to access, enforced at the semantic layer.
SQL you already know
Query Cube from Preset using standard SQL. No new languages to learn—just connect and start building dashboards.
40+ visualization types
Bring Cube's governed metrics to life with Preset's rich visualization library. Charts, maps, pivot tables, and more.
Open ecosystem
Both Cube and Preset are built on open-source foundations. No vendor lock-in, full flexibility, active communities.
Learn More
Cube Docs: Apache Superset
Official Cube documentation for connecting to Apache Superset™ and Preset.
Learn more →Cube Docs: Semantic Layer Sync with Preset
Automatically sync your Cube semantic layer to Preset datasets.
Learn more →Video: Implementing Preset's Data Access Roles in Cube
Learn how to implement Preset's data access roles with Cube for row-level security.
Learn more →Cube + Preset FAQ
No. Preset works great with direct database connections. Cube is an optional layer that adds consistent metric definitions, caching, and governance. It's valuable for organizations that need a single source of truth for metrics.
Yes. Connect Cube as a database in Preset and you can query it from SQL Lab just like any other data source. This is great for ad-hoc analysis using governed metrics.
Deploy Cube and define your data model, then add Cube as a database connection in Preset using Cube's SQL API endpoint. Our blog posts have detailed tutorials.
Preset has built-in metrics and calculated columns at the dataset level. Cube provides a more comprehensive semantic layer that can serve multiple BI tools. Many teams use both—Cube for organization-wide governance and Preset's layer for dashboard-specific calculations.
Get in Touch
Get started with 5 users free forever. Connect to Cube or your data warehouse directly and start building dashboards. Fill out the form and we'll be in touch.