From Power BI to Holistics
This document was written in May 2026, and may have become inaccurate as Holistics and Power BI continue to improve their products.
Introduction
This section helps existing Power BI users transition to Holistics. It maps familiar Power BI concepts (semantic models, DAX measures, reports, workspaces) to their Holistics equivalents, and walks through a practical migration path.
If you're new here, start with the Conceptual Differences page, then move on to the Migration Overview when you're ready to plan the move.
High level similarities
Both Power BI and Holistics are end-to-end BI platforms that let analysts define a semantic layer once and let business users explore and visualize data on top of it. Both support:
- A modeling layer with tables/models, relationships, and reusable measures
- A self-service experience for business users to build their own visualizations
- Row-level security and governance controls over what each user can see
- Embedded analytics for delivering dashboards inside other applications
- As-code project formats (Power BI's
.pbip/ TMDL and Holistics' AMQL) that enable version control and code review workflows
High level differences
Architecture and compute
Power BI's default mode imports data into an in-memory VertiPaq engine that lives inside the .pbix/semantic model and is refreshed on a schedule. Holistics, by contrast, pushes every query down to your data warehouse at runtime — there's no separate copy of the data to manage, no refresh schedule, and the warehouse remains the single source of truth.
This has practical consequences: Power BI excels when you want fast in-memory performance on a curated extract, while Holistics excels when you want analytics that always reflect live warehouse data and want to avoid duplicating storage and refresh pipelines.
Modeling language
Power BI uses DAX for measures and calculated columns and Power Query (M) for ETL inside the file. Holistics uses AMQL — a single declarative language for models, datasets, dashboards, and metrics — plus AQL (or SQL) for defining dimensions and measures.
A key difference is that DAX measures depend on filter context that flows through relationships, while AQL measures use explicit dimension scope, which makes their behavior easier to reason about across different queries.
Project format and version control
Power BI's traditional .pbix is a binary file that doesn't diff well. The newer .pbip format exposes the semantic model as TMDL text, but report definitions remain a mix of TMDL and JSON. Holistics projects are uniform AMQL files across models, datasets, and dashboards — every change produces a clean text diff that's easy to review in Git.
Reusability
Power BI semantic models are scoped to a workspace, and reusing logic across reports often means copying tables or measures. Holistics is built around a reusability-first philosophy:
- Models are reusable across datasets
- Metrics are reusable across dashboards
- Dimensions and measures are reusable within a model
- Modules let you organize and share code across projects
Authoring tool
Power BI Desktop is the primary authoring tool and is Windows-only. Holistics provides a cross-platform web IDE and supports a local development workflow using any editor on macOS, Linux, or Windows.
Visualization and dashboards
Power BI reports bind to a single semantic model and use a fixed grid-based layout. Holistics Canvas Dashboards can span multiple datasets and use a freeform canvas where you can place tiles anywhere, layer them for visual effects, and add interactive controls next to charts.
For custom visualizations, Power BI relies on a marketplace of custom visuals written in TypeScript. Holistics uses Vega-Lite for custom charts, which is a declarative format that integrates natively with the platform's field-binding model.
Self-service analytics
Both platforms let business users build their own visualizations. Power BI offers Q&A (natural language) and the "Explore" experience. Holistics provides Dataset Explore with a drag-and-drop interface, plus built-in point-and-click controls for common needs like period comparison.
Embedded analytics
Both Holistics and Power BI support embedding dashboards into customer applications. Holistics uses JWT-based embedding, while Power BI offers Embed for your customers (app-owns-data) and Embed for your organization (user-owns-data) modes.
What's in this section
- Conceptual Differences — A side-by-side mapping of Power BI concepts to Holistics concepts, with deeper explanations of where the two platforms diverge.
- Migration Overview — A high-level guide for migrating a Power BI project to Holistics, including how to convert tables, relationships, DAX measures, calculated columns, and reports.