Best Self Hosted Alternatives to Zoho Analytics

Grafana is an open source observability and data visualization platform for querying, visualizing, and alerting on metrics, logs, and traces across many backends. It provides interactive dashboards and exploration workflows so teams can monitor systems and troubleshoot issues from a single interface.

Key Features

• Dashboards with flexible visualizations and templating for reusable views
• Explore workflows for ad-hoc querying and drilldowns across time ranges and data sources
• Unified alerting with rule evaluation and multi-channel notifications
• Pluggable data source and panel ecosystem to integrate with many metrics, log, and trace systems
• Sharing and collaboration features for teams (dashboards, annotations, and permissions)

Use Cases

• Infrastructure and Kubernetes monitoring using time-series backends
• Centralized log exploration and correlation with metrics for incident response
• Application observability by visualizing traces and service performance trends

Limitations and Considerations

• The experience and capabilities depend heavily on the chosen data sources and plugins
• Operating at very large scale can require careful tuning of storage backends and dashboard/query design

Grafana is well-suited for organizations that want a single “pane of glass” across diverse telemetry sources. Its extensible plugin model and alerting make it a common foundation for observability stacks in both homelabs and enterprise environments.

Apache Superset is an open-source, web-based business intelligence platform for exploring data and building interactive dashboards. It connects to a wide range of SQL-speaking databases and query engines and supports both no-code charting and advanced SQL workflows.

Key Features

• No-code chart builder for quickly creating visualizations
• SQL Lab (web-based SQL editor) for complex queries and analysis
• Interactive dashboards with filters, cross-filtering, and drill-down capabilities
• Semantic layer for defining reusable metrics and dimensions
• Virtual datasets for ad-hoc exploration without creating physical tables
• Extensible visualization plug-in architecture with many built-in chart types
• Configurable caching to reduce database load and improve dashboard performance
• Role-based access control and multiple authentication options
• REST API for programmatic customization and automation

Use Cases

• Self-serve analytics dashboards for business and product teams
• Exploratory SQL analysis and dataset prototyping for analysts
• Organization-wide reporting layer on top of existing data warehouses

Superset is a strong fit for teams that want a scalable BI UI on top of existing SQL data infrastructure. Its combination of no-code dashboards and a powerful SQL workspace makes it useful for both casual and advanced data users.

Metabase is an open-source business intelligence and embedded analytics platform that sits on top of your databases and lets people explore data, create visualizations, and share insights. It supports both no-code querying for non-technical users and SQL for advanced analysis.

Key Features

• Visual query builder for exploring data without writing SQL
• Native SQL editor for complex queries and reusable questions
• Interactive dashboards with filters, drill-downs, and sharing options
• Alerts and scheduled subscriptions (email/Slack) for dashboards and questions
• Data modeling features such as semantic models, metrics, and segments
• Embedded analytics via iframe embedding and an SDK for React
• Permissions, groups, and authentication integrations for controlled access

Use Cases

• Company-wide self-serve analytics on top of a production database or warehouse
• KPI dashboards and recurring reporting for teams like finance, product, and ops
• Customer-facing analytics embedded into SaaS products

Limitations and Considerations

• Some advanced capabilities (for example certain governance and enterprise features) are available only in commercial editions

Metabase is well-suited for teams that want fast, approachable analytics without building a custom reporting stack. It can scale from simple internal dashboards to embedded, multi-user analytics with access controls.

Redash is an analytics and business intelligence application for exploring data with SQL/NoSQL queries, turning results into visualizations, and sharing dashboards across a team. It is designed for browser-based collaboration so both technical and non-technical users can access and act on trusted, refreshable reports.

Key Features

• Browser-based query editor with schema browsing and autocomplete
• Visualizations and drag-and-drop dashboards built from query results
• Sharing and collaboration on queries and dashboards, including public links
• Scheduled query execution and automatic dashboard refresh
• Alerting on query results when conditions are met
• REST API for automating and integrating reporting workflows
• Broad, extensible support for many SQL and NoSQL data sources

Use Cases

• Self-hosted internal BI for SQL-driven reporting and team dashboards
• Centralized querying across multiple databases and analytics platforms
• Automated operational metrics with scheduled refreshes and alerts

Limitations and Considerations

• Primarily oriented around SQL/NoSQL querying and dashboards rather than full semantic modeling typical of some enterprise BI suites

Redash is a strong fit for teams that want a lightweight, web-based way to query many data sources, publish dashboards, and standardize reporting. Its alerting, scheduling, and API features make it useful for both interactive analysis and automated data-driven workflows.

Evidence is an open-source, code-based alternative to drag-and-drop BI tools for building interactive data products. It generates a web app from Markdown pages that run embedded SQL queries and render charts and UI components.

Key Features

• Build reports and dashboards from Markdown with embedded SQL queries
• Component-based, interactive visualizations rendered from query results
• Templated pages plus loops and conditional logic for reusable reporting
• Developer-friendly workflow designed for version control and code review
• Supports connecting to common analytical databases and warehouses

Use Cases

• Internal BI reporting portals with a narrative format (metrics plus commentary)
• Customer-facing analytics and embedded reporting in product documentation sites
• Rapid exploratory analysis shared as reproducible, versioned reports

Evidence is well-suited for teams that prefer writing SQL and keeping analytics artifacts in Git. It provides a straightforward path from queries to polished, shareable data experiences without relying on a drag-and-drop editor.

Overview Chartbrew is an open-source web application that lets teams connect to databases and APIs to build, edit, and share live charts and dashboards. It supports a chart builder, editable dashboards, and embeddable charts, with collaboration features for teams and clients.

Key Features

• Report Builder: create data-driven reports with a user-friendly interface and multiple data sources
• Chartbrew AI: converse with data to generate insights and visualizations using an AI assistant
• Data Alerts: set thresholds and get notified of anomalies or changes
• Data Update Schedule: automate regular data refreshes and reporting cadence
• Automated Dashboard Snapshots: deliver dashboards to Slack, email, or webhooks on a schedule
• Embedded Reports: embed interactive dashboards and charts into other apps or sites
• SQL Query Builder: build and refine SQL queries without writing code
• Client Accounts: manage access for teams and clients with granular permissions
• Webhooks & API: automate workflows and integrations with external tools
• Dashboard Templates: reuse and scale client dashboards with templated designs
• Integrations: connect to a wide range of data sources and services
• Multi-tenant collaboration: support team-wide sharing and collaboration on dashboards

Use Cases

• Internal analytics: create KPI dashboards and real-time monitoring across multiple data sources for teams
• Client reporting: prepare branded, template-driven dashboards for multiple clients with secure access
• Embedded analytics: integrate charts and dashboards into existing products or portals via embedding

Conclusion Chartbrew combines a visual chart/dashboard builder with AI-powered insights, collaboration, and flexible data source connections. As an open-source platform, it supports self-hosted deployments, client reporting needs, and automated workflows to streamline analytics across teams and clients.

Cially is an open-source analytics dashboard for Discord servers that combines a bot, an API, and a full-stack web application to surface real-time insights and historical statistics about server activity. It captures events, stores structured records, and resolves IDs to human-readable entities to present engagement and growth metrics.

Key Features

• Real-time collection of Discord events via a dedicated bot and internal API
• Message analytics, activity insights, and growth/engagement metrics for servers
• Full-stack Next.js web dashboard with user search, UI customization, and reports
• Pocketbase-backed storage providing a lightweight embedded database and auth
• ID resolution between bot and web app so names and latest states are always accurate
• Docker-friendly deployment and configuration for self-hosted environments
• Privacy-first defaults: message content is not stored unless explicitly enabled

Use Cases

• Community managers tracking message activity, peak times, and member engagement
• Moderators auditing joins/leaves and activity trends to inform moderation policies
• Server owners measuring growth and the impact of events, campaigns, or changes

Limitations and Considerations

• License restricts commercial use (Attribution-NonCommercial-NoDerivs 2.0), which may limit some deployments
• Designed for small-to-medium servers; very large servers may require tuning or more robust storage/retention strategies

Cially is suitable for teams and communities that need transparent, privacy-conscious analytics for Discord. It focuses on actionable metrics and simplifies deployment for self-hosting while prioritizing control over collected data.

Edalitics (EDA) is an open-source, metadata-driven analytics and dashboard platform designed to make data exploration and visualization accessible to non-technical users while providing advanced features for analysts. It pairs a TypeScript/Node.js backend with an Angular frontend and stores metadata and configuration in MongoDB.

Key Features

• No-code dashboard and report creation with a responsive, modern UI
• Advanced SQL query mode for power users to build custom queries
• Tree-mode data model explorer to navigate logical data models
• KPI definitions and automated e-mail alerts for monitoring
• Public dashboards shareable via URL for read-only access
• Row Level Security (RLS) to restrict data access per user or role
• Metadata and configuration stored in MongoDB
• Official Docker image and deploy templates (Helm/docker) for quick deployment

Use Cases

• Business intelligence and executive dashboards for product, sales, or operations teams
• Self-service reporting for non-technical stakeholders with an option for SQL-based custom reports
• KPI monitoring and automated alerting for operational or business metrics

Limitations and Considerations

• Licensed under AGPL-3.0, which may impose obligations for commercial redistribution or embedding in proprietary systems
• Metadata storage relies on MongoDB; organizations that prefer relational metadata stores may need adaptation
• Connector and integration coverage may be narrower than mature commercial BI platforms; advanced integrations can require additional configuration or development

Edalitics provides a lightweight, metadata-first approach to building dashboards and reports with a balance of no-code tooling and SQL power features. It is suited for teams that want fast self-service analytics with built-in KPI alerting and access controls.