Exploring Deepnote, Grafana & Visivo

Deepnote Vs. Grafana Vs. Visivo

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

Feature	Deepnote	Grafana	Visivo
Deployment Model	Cloud (browser-based), Enterprise deployment, Private cloud	Open-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hosted	Open-source, Cloud Service, Self-hosted
Pricing	Free tier (limited projects); paid for premium features. Closed-source.	OSS 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.

Tool	Deployment Model	Pricing	Cost
Deepnote	Cloud (browser-based), Enterprise deployment, Private cloud	Free tier (limited projects); paid for premium features. Closed-source.	$$$
Grafana	Open-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hosted	OSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).	$$
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.

Deepnote

Data science teamsEducatorsAnalysts collaborating on notebooks

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.

Deepnote

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.

Deepnote

SQL databases (PostgreSQL, BigQuery, etc.)Cloud storage (Google Drive, S3)dbt workflow 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.

Tool	AI Features
Deepnote	❌
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.

Deepnote

Jupyter-like notebooks with collaborative editing. Supports interactive visualizations by writing code (Python, R, SQL blocks). Has a GUI for basic charts: you can switch a SQL cell's results into a chart view (bar/line) quickly. Can arrange outputs into a dashboard layout for sharing. Custom viz requires coding (e.g., Plotly, seaborn).

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.

Deepnote

+ Real-time collaboration on notebooks (like Google Docs for Jupyter) – multiple users can work simultaneously. Great for mixed code-and-text narratives and then turning into lightweight dashboards for stakeholders.

− Still requires coding for most analysis; not a drop-in replacement for tools like Tableau for a pure business user.

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.

Deepnote

DB Access: Yes, uses direct credentials to query databases in SQL cells. Virtualization: No separate layer – it's a client executing queries or code. Push: No (though you could push data via Python in a notebook to an external system). Other: Deepnote runs in cloud with project-specific isolation; offers Google SSO. Not designed for role-based consumption – notebooks can be shared via link with view/edit rights.

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.

$pip install visivo