Exploring Looker Studio, Apache Superset & Visivo

Looker Studio vs. Apache Superset vs. Visivo

Compare key features, capabilities, and differentiators between Looker Studio, Apache Superset, Visivo. This comprehensive analysis will help you make an informed decision for your data visualization needs.

Quick Comparison

Key features and capabilities at a glance

Feature	Looker Studio	Apache Superset	Visivo
Deployment Model	Cloud (Google Cloud), Enterprise deployment, Private cloud	Self-host (Apache OSS), Preset Cloud (managed), Docker deployment	Open-source, Cloud Service, Self-hosted
Pricing	Free to use (with Google account); Pro version for enterprise (Looker Studio Pro) introduced with SLAs.	Open-source (Apache 2.0); Preset Cloud offers paid hosting/support	Open source (GPL-3.0)
Cost	$	$	$
Git Integration
CI/CD & Testing
Real-time
AI Features
Visual to Code
DAG-Based

Target Users & Use-Cases

Each BI tool is designed with specific user personas in mind.

Looker Studio

Business usersMarketersGoogle ecosystem users

Apache Superset

Data analystsSQL-savvy business usersData engineers

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

Development experience directly impacts team productivity and time-to-value.

Looker Studio

2/5

Apache Superset

3/5

Visivo

5/5

Key Integrations & Ecosystem

A robust ecosystem of integrations is essential for modern BI tools.

Looker Studio

500+ data connectorsGoogle products (Analytics, Ads)SQL databases via Simba drivers

Apache Superset

SQL databases via SQLAlchemyAuthentication systems (OAuth, LDAP)dbt outputs as data sources

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

Visualization Capabilities

The ability to create compelling visualizations is key to data storytelling.

Looker Studio

Drag-and-drop report editor. Offers charts like time series, bar, geo maps, tables. Customization is decent (colors, labels), though not as fine-grained as Tableau. Supports community visualizations (bring custom JS charts). Layout is canvas-style – good for dashboards and infographics.

Apache Superset

Rich set of visualizations (bar, line, time-series, big number, etc.) via built-in plugins. Dashboards support filters and cross-highlighting. Customization is decent (colors, chart options) but not as polished as Tableau. Can create custom viz plugins with React/D3 if needed.

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform's unique strengths and limitations.

Looker Studio

Completely free for most use-cases. Extremely easy for simple needs – non-tech users can create a shareable dashboard in minutes. Being Google, sharing and embedding is seamless.

Lacks advanced analytics (no calculated fields beyond basic formulas, limited data shaping). Performance can suffer on large data sets unless using aggregated extracts. No row-level security (one report = one set of credentials or extracted data).

Apache Superset

Open-source BI with no vendor lock-in. Large community and improving UI. Suitable for embedding into internal tools.

Setup and maintenance require engineering effort (Docker, config). UI can be less intuitive for non-technical users; SQL knowledge often needed for custom queries.

Visivo

BI-as-code approach enables version control, collaboration, and CI/CD workflows. DAG-based architecture provides powerful data transformation capabilities and dependency management. Seamless visual-to-code workflow allows both technical and non-technical users to build dashboards effectively.

Requires understanding of data concepts; not a pure drag-and-drop tool like Tableau. Initial setup requires technical knowledge for optimal configuration.

Security & Architecture

Critical considerations for enterprise deployments.

Looker Studio

DB Access: Yes, live connects to sources using provided credentials (or OAuth tokens). Option to cache query results in Google's cache for performance. Virtualization: Data remains in source or cache – Data Studio doesn't store data persistently (except cached). Push: No, it pulls data when rendering charts. Other: Uses Google account auth for access; you can manage view/edit permissions on reports. Lacks fine security on data level (you'd need separate reports or filters per audience).

Apache Superset

DB Access: Yes, connects directly to databases with provided creds (queries run in DB). Virtualization: No internal data storage beyond caches – queries are delegated to sources. Push: No, data is pulled via queries on demand or scheduled caching. Other: Supports row-level security filters and role-based access to datasets/dashboards. Uses your DB's security for data access (you supply read-only creds).

Visivo

No db access required. Very strong security features due to the DAG-based access controls and the push based deployment model.

Why Visivo Stands Out

While each platform has its strengths, Visivo offers unique advantages for modern data teams.

DAG-Based Architecture for complex data transformations

Visual to Human-readable Code conversion

Multiple development approaches for all skill levels

AI-Powered dashboard creation

Full Git integration and version control

Open-source with enterprise features

Ready to Experience Modern BI?

Try Visivo today and see how it transforms your data analytics workflow.

$ curl -fsSL https://visivo.sh | bash

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