Exploring Metabase, Streamlit & Visivo

Metabase Vs. Streamlit Vs. Visivo

In this article, we'll compare the key features, capabilities, and differentiators between Metabase, Streamlit, Visivo. This comprehensive comparison will help you make an informed decision about which platform best suits your data visualization and analytics needs.

Quick Comparison

A high-level overview of key features and capabilities across these BI tools. This comparison helps you quickly identify which platform best matches your needs.

FeatureMetabaseStreamlitVisivo
Deployment ModelSelf-host OSS (Java), Metabase Cloud (hosted SaaS), Docker deploymentOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseOpen-source, Cloud Service, Self-hosted
PricingOpen-source core (AGPL v3); Enterprise features in paid plansOpen-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hostingOpen source (GPL-3.0)
Cost$$$$
Git Integration✔️
CI/CD & Testing✔️
Real-time
AI✔️
Visual to Code✔️
DAG-Based✔️

Deployment & Pricing

Understanding the deployment options and pricing structure is crucial for making an informed decision. Here's how each platform handles deployment and what you can expect in terms of costs.

ToolDeployment ModelPricingCost
MetabaseSelf-host OSS (Java), Metabase Cloud (hosted SaaS), Docker deploymentOpen-source core (AGPL v3); Enterprise features in paid plans$$
StreamlitOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseOpen-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hosting$
VisivoOpen-source, Cloud Service, Self-hostedOpen source (GPL-3.0)$

Target Users & Use-Cases

Each BI tool is designed with specific user personas in mind. Understanding the target audience helps ensure you choose a platform that aligns with your team's skills and needs.

Metabase

Non-technical business usersProduct teamsData teams for quick analytics

Streamlit

Data scientistsPython developersML engineers

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

The development experience can significantly impact your team's productivity. This section compares how easy it is to build, deploy, and maintain dashboards in each platform.

Metabase

Streamlit

Visivo

Key Integrations & Ecosystem

A robust ecosystem of integrations is essential for modern BI tools. Here's how each platform connects with other tools in your data stack.

Metabase

Major SQL databasesNoSQL databases (MongoDB, Druid)dbt metadata via community plugin

Streamlit

Python data science librariesSQL databasesSnowflake native integration

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

AI & Advanced Features

Artificial intelligence is transforming how we interact with data. Compare the AI capabilities and advanced features offered by each platform.

ToolAI Features
Metabase
Streamlit
Visivo✔️

Visualization Capabilities

The ability to create compelling and insightful visualizations is a key differentiator between BI tools. Here's how each platform handles data visualization.

Metabase

Simplified UI: users can create questions (queries) via a point-and-click interface or SQL editor. Visualizations cover basic needs (bar, line, pie, maps, etc.). Dashboards allow filter widgets to link multiple cards. Customization is basic – focus is on quick insights over polished design.

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.

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform has its own strengths and weaknesses. Here's a detailed breakdown of what sets each tool apart, including both advantages and limitations.

Metabase

+ Extremely easy for non-technical users to ask questions – great for self-service on simple queries.
− No semantic layer – each "question" is standalone, which can lead to inconsistent metrics if not careful. Lacks advanced visuals and fine formatting; not ideal for complex dashboards or large-scale governance.

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).

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

Security and architecture are critical considerations for enterprise deployments. Here's how each platform handles data security and system architecture.

Metabase

DB Access: Yes, Metabase connects directly to each data source to run queries. Virtualization: No intermediate layer – it's live queries (with caching). Push: No (pull-based queries; can cache results in application DB). Other: Supports row-level security with query filters (enterprise). Offers auditing of questions run. Embedding to apps with signed tokens available (with its own permissions).

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.

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 that make it an excellent choice for modern data teams.

  • DAG-Based Architecture: Enables complex data transformations and dependencies
  • Visual to Human-readable Code: Seamlessly switch between visual and code-based development
  • Ease of Development: Multiple approaches to build for both technical and non-technical users
  • AI-Powered Development: Leverage AI to accelerate dashboard creation
  • Git Integration: Full version control and collaboration capabilities

Ready to experience the power of modern BI? Try Visivo today and see how it compares to other tools in your stack.

$ curl -fsSL https://visivo.sh | bash
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Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
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How can I help? This connects to our slack so I'll respond real quickly 😄
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