Exploring Streamlit, Preset & Visivo

Streamlit Vs. Preset Vs. Visivo

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

Feature	Streamlit	Preset	Visivo
Deployment Model	Open-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterprise	Cloud (multi-tenant), Cloud (VPC), Managed service	Open-source, Cloud Service, Self-hosted
Pricing	Open-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hosting	Managed service (subscription per creator & usage). Underlying Superset is Apache-licensed.	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.

Tool	Deployment Model	Pricing	Cost
Streamlit	Open-source (Python library), Self-hosted server, Streamlit Cloud, Snowflake-managed enterprise	Open-source (Apache 2.0); Free community hosting (limited), Snowflake-managed enterprise hosting	$
Preset	Cloud (multi-tenant), Cloud (VPC), Managed service	Managed service (subscription per creator & usage). Underlying Superset is Apache-licensed.	$$$
Visivo	Open-source, Cloud Service, Self-hosted	Open 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

Preset

Data teams wanting managed SupersetOrganizations without resources to self-hostEnterprise analytics teams

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

Preset

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

Preset

Same database integrations as Supersetdbt Cloud for metadataOAuth connections to popular DBs

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.

Tool	AI Features
Streamlit	❌
Preset	❌
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.

Preset

Identical visualization capabilities to Apache Superset (Preset is built on Superset) – plus a nicer UI/UX and theme. Custom visualizations can be added via Preset's marketplace.

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).

Preset

+ Easiest way to use Superset – fully managed infrastructure and support from Superset experts. New features and custom connectors often available.

− Still catching up to feature parity with mature BI tools in terms of collaboration (Git, fine-grained content permissions).

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.

Preset

DB Access: Yes (your databases' credentials are stored in Preset; it queries them directly). Virtualization: No, live queries on sources (with optional result caching). Push: No – you supply data to your DB, Preset pulls on viz. Other: Managed security – SSO integration, teams/roles setup in UI. Data stays in your cloud DB; Preset does not persist data (aside from cached query results).

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.

$pip install visivo