Exploring Streamlit, Grafana & Visivo

Streamlit Vs. Grafana Vs. Visivo

In this article, we'll compare the key features, capabilities, and differentiators between Streamlit, Grafana, 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.

FeatureStreamlitGrafanaVisivo
Deployment ModelOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseOpen-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hostedOpen-source, Cloud Service, Self-hosted
PricingOpen-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hostingOSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).Open 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
StreamlitOpen-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterpriseOpen-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hosting$
GrafanaOpen-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hostedOSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).$$
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.

Streamlit

Data scientistsPython developersML engineers

Grafana

DevOps engineersIT monitoring teamsData engineers for time-series analytics

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.

Streamlit

Grafana

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.

Streamlit

Python data science librariesSQL databasesSnowflake native integration

Grafana

Time-series databases (Prometheus, InfluxDB)SQL databases and cloud metricsAlerting systems (PagerDuty, Slack)

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
Streamlit
Grafana
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.

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.

Grafana

Optimized for time-series and metrics visualizations (graphs, gauges, alerts). Supports logs and traces panels too. Basic charts for category data exist but not Grafana's strong suit. Highly customizable dashboards via JSON config or UI. Many community panels (plugins) to extend visualization types.

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.

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).

Grafana

+ Best for operational dashboards – combining metrics, logs, and traces in one UI (especially with Grafana Cloud). Very extensible via plugins.
− Not designed for ad-hoc business analytics on arbitrary data – e.g., no built-in SQL query builder for relational data (user must write queries or use other tools to prepare data). Visualizations not as geared for presentation (more for investigation).

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.

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.

Grafana

DB Access: Yes, connects directly to data sources (or through its agents). Virtualization: More like federation – it queries multiple backends via plugins. Push: Metric data is often pushed into time-series DBs which Grafana then reads – so indirectly yes (in monitoring use-cases). Grafana itself pulls from those DBs. Other: Auth via LDAP/OAuth. Granular permissions on dashboards and data sources. Encryption and other enterprise security features in paid version.

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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