Exploring Preset, Mode & Visivo

Preset vs. Mode vs. Visivo

Compare key features, capabilities, and differentiators between Preset, Mode, 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

Feature	Preset	Mode	Visivo
Deployment Model	Cloud (multi-tenant), Cloud (VPC), Managed service	Cloud (SaaS), Enterprise deployment, Private cloud	Open-source, Cloud Service, Self-hosted
Pricing	Managed service (subscription per creator & usage). Underlying Superset is Apache-licensed.	Subscription per user (tiered features). Proprietary.	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.

Preset

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

Mode

Data analystsData scientistsBusiness teams consuming insights

Visivo

Analytics EngineersData teamsBusiness usersEngineers

Ease of Development & Deployment

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

Preset

4/5

Mode

3/5

Visivo

5/5

Key Integrations & Ecosystem

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

Preset

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

Mode

Multiple SQL databasesPython/R for advanced analyticsAPI and webhooks for automation

Visivo

dbt coreAll major databasesCustom connector frameworkSlack for alertsGithub

Visualization Capabilities

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

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.

Mode

Hybrid analytics: Start with SQL query, then seamlessly use results in a Python or R notebook within Mode. Visualizations: either use the built-in chart builder on query results (which is simple but covers basics), or output custom plots from the notebook (Matplotlib, etc.). You can combine these in a report. Good for analytical narratives.

Visivo

Highly custom UI with easy defaults

Detailed Differentiators

Each platform's unique strengths and limitations.

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).

Mode

Combines analytics workflows: SQL + Python/R in one tool, enabling advanced analysis (statistical, ML) with sharing in one place. Great collaboration – team commentary and shareable, embeddable reports.

Not aimed at strict self-service for non-analysts (business users usually consume results, not build). Lacks a governed semantic layer – relies on analysts to maintain consistency.

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.

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).

Mode

DB Access: Yes, Mode executes queries against your DB whenever a report refreshes. Virtualization: No separate layer – it's basically a client querying the DB. Push: No, except you can schedule exports of results to external systems. Other: Row-level security must be implemented in SQL (no built-in feature for it). Supports SSO and fine-grained access to reports (who can view/edit).

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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