The Better Lightdash

If you want a BI tool that is architecturally similar to Looker, but more affordable and well-integrated with dbt, go for Lightdash.

If you want a BI tool that is architecturally similar to Looker, but more affordable, well-integrated with dbt, and mature in functionalities, go for Holistics.

Don't just take our word for it - here's what the analytics community said

Lightdash is great, but it might not be mature enough for some
Thorough analysis of Lightdash vs Other Alternatives

How Holistics Work?

With Holistics, analysts define and maintain metrics definition in a central semantic layer. These metrics are exposed to business users in simple drag-and-drop interface. This allows everyone to analyze and explore data on their own without relying on data analysts.

At the heart of Holistics is AMQL (Analytics Model & Query Language). AMQL enables analysts to define reusable analytics logic using code, an experience familiar to most developers. Your entire analytics pipeline can be serialized into code and checked into Git version control.

Holistics's AMQL

Holistics’ key functionalities include:

  • Semantic Modeling Layer: Analysts define dimensions and measures of business logic in a central semantic layer. These logic can be reused in multiple places. Because logic is defined as code, analysts can use their favorite IDE to do "analytics programming".
  • dbt integration: Holistics integrate deeply with dbt, allowing metadata from dbt to be surfaced to BI layer.
  • Git Version Control: Through Git version controls: pull requests, protected branches, and merging into masters. Know who changes what when.

Self-Service Analytics layer: Analysts prepare curated datasets and share them with non-technical users for self-service exploration. Because analytic logic is carefully maintained and curated, business users can feel trusted with the data.

Some of Holistics’ self-service functionalities are:

  • Native Period-over-Period Comparison.
  • Custom Charts and a wide variety of visualization options.
  • Cross-Filtering and Drill-through.
  • Custom Alerts.
  • Embedded Analytics and White Labeling.
  • Custom Alerts and Push Notifications.
  • Sharing reports via Slack, Emails, Shareable Links.
  • API available.

Lightdash vs Holistics: Side-by-Side Comparison

Aspect Lightdash Holistics
High-level Approach Take a similar approach: 1. Analysts define reusable metrics using code (DSL) and check in to Git version control. 2. Business users to explore data with simple drag-and-drop interfaces.
Deployment Cloud-hosted or self-hosted Cloud hosted
Compliance Not Available. GDPR; SOC2 Type II;
Modeling Layer
Central Modeling Layer to define Business Logic Yes, plain YML. Yes. With AMQL
GUI to model data No. Only code-based interface. Yes. Dual interface (both code-based and GUI-based).
Developer Experience
Code-based approach Yes (YML) Yes (AML)
Version Control with Git Yes Yes
API No Yes
Reporting & Visualization
Self-service Exploration Yes Yes
Visualizations Limited Visualization Rich visualization
Custom Charts No Yes
Native Date Comparison No Native support with Period-over-Period Comparison
Embededed Analytics No Yes
Sharing Reports Via Slack No Yes
Pivot Table Yes More advanced, with subgroup calculation