Exploring Streamlit, Looker (Google) & Visivo

Streamlit vs. Looker (Google) vs. Visivo

Compare key features, capabilities, and differentiators between Streamlit, Looker (Google), 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

FeatureStreamlitLooker (Google)Visivo
Deployment ModelOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseCloud-hosted (Google Cloud)Open-source, Cloud Service, Self-hosted
PricingOpen-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hostingCommercial (Proprietary); enterprise pricing (no free tier)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.

Streamlit

Data scientistsPython developersML engineers

Looker (Google)

Enterprise OrganizationsGoogle Cloud Accounts

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

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

Streamlit

5/5

Looker (Google)

2/5

Visivo

5/5

Key Integrations & Ecosystem

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

Streamlit

Python data science librariesSQL databasesSnowflake native integration

Looker (Google)

Google CloudGoogle AnalyticsGoogle Sheets

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

Visualization Capabilities

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

Streamlit

Not a traditional BI dashboard tool – rather, a Python app framework. You write Python to output charts, tables, and UI widgets. Highly flexible (use any Python viz library like Altair, Plotly, etc.), but all customization is via code.

Looker (Google)

Robust web dashboards and exploratory interface. Good selection of chart types; custom visualizations via plugins or custom code. Highly customizable via LookML for data logic, but visual formatting is UI-driven (some limitations vs. Tableau).

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform's unique strengths and limitations.

Streamlit

Super easy and fast to turn a Python script into a shareable web app. Perfect for quickly prototyping data apps and internal tools.
Not aimed at non-coders – lack of GUI means business users won't build in it. No built-in multi-user management or security layers (rely on external auth if needed).

Looker (Google)

LookML semantic layer – centralized metrics definitions ensure a 'single source of truth'. Strong governance (row-level security, permissions) and embedded analytics support.
Requires upfront modeling (learning LookML); expensive. Visual customization and ad-hoc analysis flexibility less than Tableau/PowerBI.

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.

Streamlit

DB Access: Yes, if app connects to a DB, it uses direct credentials (no abstraction). Virtualization: No, Streamlit just runs code – any virtualization must be coded. Push: No – app pulls data or receives via API. Other: Security depends on deployment (can use authentication proxies or Snowflake's SSO when integrated). No built-in row-level security – must code filters per user if needed.

Looker (Google)

DB Access: Yes (direct read queries to DB with cached results). Virtualization: No internal engine – relies on source DB ('in-database' analytics). Push: No, pull-based queries (though persistent derived tables can be pushed into DB). Other: Fine-grained RBAC; row-level security; SSO/SAML support.

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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