Exploring Grafana, Apache Superset & Visivo

Grafana Vs. Apache Superset Vs. Visivo

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

FeatureGrafanaApache SupersetVisivo
Deployment ModelOpen-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hostedSelf-host (Apache OSS), Preset Cloud (managed), Docker deploymentOpen-source, Cloud Service, Self-hosted
PricingOSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).Open-source (Apache 2.0); Preset Cloud offers paid hosting/supportOpen 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.

ToolDeployment ModelPricingCost
GrafanaOpen-source (AGPLv3), Grafana Enterprise, Grafana Cloud, Self-hostedOSS free; Grafana Enterprise (paid add-ons); Grafana Cloud (free tier & paid).$$
Apache SupersetSelf-host (Apache OSS), Preset Cloud (managed), Docker deploymentOpen-source (Apache 2.0); Preset Cloud offers paid hosting/support$
VisivoOpen-source, Cloud Service, Self-hostedOpen 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.

Grafana

DevOps engineersIT monitoring teamsData engineers for time-series analytics

Apache Superset

Data analystsSQL-savvy business usersData engineers

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.

Grafana

Apache Superset

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.

Grafana

Time-series databases (Prometheus, InfluxDB)SQL databases and cloud metricsAlerting systems (PagerDuty, Slack)

Apache Superset

SQL databases via SQLAlchemyAuthentication systems (OAuth, LDAP)dbt outputs as data sources

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.

ToolAI Features
Grafana
Apache Superset
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.

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.

Apache Superset

Rich set of visualizations (bar, line, time-series, big number, etc.) via built-in plugins. Dashboards support filters and cross-highlighting. Customization is decent (colors, chart options) but not as polished as Tableau. Can create custom viz plugins with React/D3 if needed.

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.

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).

Apache Superset

+ Open-source BI with no vendor lock-in. Large community and improving UI. Suitable for embedding into internal tools.
− Setup and maintenance require engineering effort (Docker, config). UI can be less intuitive for non-technical users; SQL knowledge often needed for custom queries.

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.

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.

Apache Superset

DB Access: Yes, connects directly to databases with provided creds (queries run in DB). Virtualization: No internal data storage beyond caches – queries are delegated to sources. Push: No, data is pulled via queries on demand or scheduled caching. Other: Supports row-level security filters and role-based access to datasets/dashboards. Uses your DB's security for data access (you supply read-only creds).

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.

$ curl -fsSL https://visivo.sh | bash
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Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
Jared Jesionek (co-founder)
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