Exploring Holistics, Deepnote & Visivo

Holistics vs. Deepnote vs. Visivo

Compare key features, capabilities, and differentiators between Holistics, Deepnote, 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

FeatureHolisticsDeepnoteVisivo
Deployment ModelCloud SaaS (Holistics 4), On-prem enterprise, Private cloudCloud (browser-based), Enterprise deployment, Private cloudOpen-source, Cloud Service, Self-hosted
PricingCommercial (proprietary). Free trial available.Free tier (limited projects); paid for premium features. Closed-source.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.

Holistics

Data teams (analytics engineers)Business users exploring defined dataData-driven organizations

Deepnote

Data science teamsEducatorsAnalysts collaborating on notebooks

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

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

Holistics

3/5

Deepnote

4/5

Visivo

5/5

Key Integrations & Ecosystem

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

Holistics

SQL databases (Snowflake, BigQuery, PostgreSQL, etc.). dbt integration: Yes – can import dbt models and exposures, aligning Holistics model with dbt transforms.SQL databases (SnowflakeBigQueryPostgreSQLetc.). dbt integration: Yes – can import dbt models and exposuresaligning Holistics model with dbt transforms.

Deepnote

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

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

Visualization Capabilities

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

Holistics

Combines a code-based 'data modeling layer' with a drag/drop UI for end users. Data team defines datasets, dimensions, measures in YAML (or UI), then business users create charts by selecting those fields. Visualization options cover common needs (charts, pivots) with moderate customization. Focus is on accuracy & consistency over flashy visuals.

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).

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform's unique strengths and limitations.

Holistics

Unified metrics layer: define once in code, use anywhere – similar to LookML but using SQL and a simpler DSL. This ensures a single source of truth across charts.
Requires data modeling effort upfront; not as plug-and-play. Smaller community (less third-party resources than bigger tools).

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.

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.

Holistics

DB Access: Yes, queries run on your DB. Optionally can cache query results in its warehouse for speed. Virtualization: Holistics does not store data long-term; it queries live or caches in temp tables. Push: No, it's pull (with ability to schedule cache refresh). Other: Supports row-level security definitions in the modeling layer; robust role-based view permissions.

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.

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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