Exploring Mode, Grafana & Visivo

Mode Vs. Grafana Vs. Visivo

In this article, we'll compare the key features, capabilities, and differentiators between Mode, 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	Mode	Grafana	Visivo
Deployment Model	Cloud (SaaS), Enterprise deployment, Private cloud	Open-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hosted	Open-source, Cloud Service, Self-hosted
Pricing	Subscription per user (tiered features). Proprietary.	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
Mode	Cloud (SaaS), Enterprise deployment, Private cloud	Subscription per user (tiered features). Proprietary.	$$$$
Grafana	Open-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hosted	OSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).	$$
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.

Mode

Data analystsData scientistsBusiness teams consuming insights

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.

Mode

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.

Mode

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

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
Mode	❌
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.

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.

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.

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.

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.

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).

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