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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.
Variety of Visualizations
25 visualization options. Custom visualizations (box plot, histogram, etc) are also available - enabled by Vega-lite integration.
16 basic visualization options.
How non-technical users self-serve
Via drag-n-drop report builder. Users explore data and build dashboards using curated datasets - which are maintained and governed by the data team for better accuracy and consistency.For every report, Executed Query is shown for validation if needed.
Via a graphical query builder (Metabase's Question). Users still have to pick and join data, filter, and perform group-by and summary before creating a visualization.No drag-and-drop interface. No SQL code surfaced for validation.
Row Limits
Up to 1,000,000 rows for Data Exploration / Report Creation (i.e., in each chart). Can export full data into CSV/Excel file.
The download limit is 1 million. Display limit: 2,000 without aggregation, and 10,000 with aggregation.
Report sharing
More advanced. Push dashboards to Slack, Email, Google Sheets, SFTP, and Webhooks.
Push dashboards to Slack and email.
Data Alerts
Available and more advanced. Comes with Dashboard Filters and Business Calculations.
Available, but with limited options.
Access Control for Embedded Dashboard
Yes, easy to use and easy to share. Better access control with row-level permission settings. Detailed documentation about embedded analytics security.
Limited - with only filter-based restrictions available. Documentation regarding this aspect is relatively sparse.
Public Shareable Link
Available with more advanced configuration. Permission settings for Dataset, Data models, Fields. Password protection also available.
Available but not secure. The only option to control public shareable links is to manually disable/enable them.
Click Behavior for Embedded Dashboards
Viewers can change filters or drill through to navigate between widgets and reports within an embedded dashboard.
Viewers can change filters only.
Semantic Layer for metric definitions
Available. Semantic Layer allows analysts to manage business logic centrally and define reusable data models.
Not available. But can work around this limitation by integrating Metabase with Cube
Reusing common SQL queries
Available. Analysts easily define reusable SQL queries for data exploration.
No. As more and more queries are added, data team ends up with repeated SQL queries all over the place, making it difficult to know where the correct version is.
Write analytics as code
Yes. Analysts can define business logic and data models as code using Holistics AML- which allows analytics logic to be governed with Git Version control, enables code review, and most importantly, promotes reusability.
No. Metabase is not designed for a code-based analytics workflow.
dbt integration
Available
Available.
Data modeling
Analysts define business metrics using SQL formulas, then map relationships between tables and transform raw tables into reusable data models for consistent usage. Can use both GUI and code view for modeling.
Analysts add metadata to database tables and specify relationships, using a graphical UI.
User Access Control
Supported both Row-level Permission and Column-level Permission.
Row-level Access Control is available in Enterprise Plan. Column-level Permission is not supported.
Usage Monitoring
Usage monitoring dashboard is available for admins to have a bird-eye view of who using what.
Not Available.
Version Control
Yes. With Git Integration.
Compliance and security
GDPR, SOC2 Type II.
How do I extract my report definitions data out of Holistics in the future?
Is Holistics EU-compliant? Do you guys have GDPR?
Is Holistics SOC2 compliant?
How easy is it to learn Holistics? Does it require advanced training or can users pick it up quickly within few hours?
What SQL data sources do you support?
I'm based in the US/Europe. Will customer support be a problem?