Love Metabase's SQL-native simplicity but hitting its ceiling? Holistics gives you the same developer-friendly foundation with a proper semantic layer, governed self-service, and Git version control — so your BI scales with your organization.
Business users explore data through curated, drag-and-drop datasets instead of relying on prepared SQL questions, freeing analysts from the ad-hoc request queue.
Define metrics and business logic once in a shared modeling layer, eliminating the scattered SQL definitions that cause 'same metric, different numbers' across reports.
Define data models as code using Holistics AML, check them into Git, and track every change with full audit trails — something Metabase simply doesn't offer.
Build once and reuse across reports. No more duplicated SQL queries scattered across your system that become impossible to update at scale.
Go beyond Metabase's 16 chart types with 25+ visualization options, custom Vega-lite charts, and advanced sharing to Slack, Email, Google Sheets, SFTP, and Webhooks.
We did set it up and build our first dashboard on Metabase. It's a solid BI tool, especially given it's FOSS, but it posed two main issues for us -- (1) limited customisability of visualisations (limiting the complexity of the information you can show) and (2) not enough features for query maintainability, as you add more and more queries that you want to share and re-use across a growing org. Holistics beat it out on both fronts.
Soroush Pour, Head of Engineering, VowFood
Non-technical users can build their own dashboards with a simple drag-and-drop UI, governed by centralized data logic.
Holistics allows you to define data models as code, and check them in to Git version control.
Define custom measures and formulas in Holistics for exploration.
With Holistics, data teams manage a central definition of business metrics and data logic in a code-based modeling layer.
Business users build their own reports and get accurate analytics in a curated environment, without having to learn SQL. Dashboards and data logic can also be serialized into code and checked into Git version control repository.
