Microsoft Power BI

Best Self Hosted Alternatives to Microsoft Power BI

A curated collection of the 3 best self hosted alternatives to Microsoft Power BI.

Microsoft Power BI is a cloud-based business analytics service that provides interactive data visualization, reporting, and dashboards. It connects to diverse data sources, transforms data, and delivers insights to support data-driven decision-making across organizations.

Alternatives List

#1
Apache Superset

Apache Superset

Apache Superset is an open-source BI platform for SQL analytics, interactive dashboards, rich visualizations, strong security, and wide database connectivity.

Apache Superset screenshot

Apache Superset is a web-based business intelligence and data exploration platform for building interactive dashboards and running ad-hoc SQL analysis on many data sources. It is designed for organizations that need a scalable BI layer with governance features like permissions and row-level security.

Key Features

  • Rich visualization library and dashboard builder with interactive filtering and drill-down
  • SQL Editor (SQL Lab) for ad-hoc querying, saved queries, and result exploration
  • Broad database connectivity via SQLAlchemy (works with many SQL engines/warehouses)
  • Semantic layer concepts via datasets/metrics and calculated columns to standardize definitions
  • Role-based access control (RBAC) with granular permissions and optional SSO integration
  • Row-level security (RLS) rules to restrict data visibility per user/role
  • Alerts & reports (scheduled delivery) and caching support for performance
  • Extensible architecture: custom visualizations/plugins and a REST API for automation

Use Cases

  • Build internal BI dashboards for product, finance, and operations teams
  • Enable analysts to explore warehouse data with governed, reusable datasets/metrics
  • Provide a lightweight alternative to commercial BI tools for SQL-centric organizations

Limitations and Considerations

  • Requires operational dependencies (metadata DB and typically Redis/Celery for async tasks)
  • Feature depth and UX may vary by database/engine depending on driver capabilities

Apache Superset is a strong fit when you need a flexible, SQL-first analytics UI with dashboards and governance controls. Its broad connector ecosystem and extensibility make it suitable from small teams to large deployments when paired with a robust data warehouse.

69.8kstars
16.5kforks
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#2
Metabase

Metabase

Self-hosted BI tool for querying data, building dashboards, and sharing insights with SQL and a no-code editor.

Metabase screenshot

Metabase is an open-source business intelligence platform for exploring data, answering ad-hoc questions, and building dashboards that can be shared across a team. It connects to many SQL databases and data warehouses, supports both a visual query builder and SQL, and can publish dashboards via embeds or public links.

Key Features

  • Visual query builder (“Notebook editor”) for non-technical users plus a full SQL editor for analysts
  • Interactive dashboards with drill-through, filtering, and parameterized questions
  • Saved questions/models and reusable query components for consistent metrics
  • Embedding options for charts/dashboards (including signed embeds in some editions)
  • Alerting and subscriptions to deliver results on a schedule (email/Slack integrations vary by setup/edition)
  • Permissions and governance features for organizing databases, schemas, and collections
  • Native caching and query performance controls (e.g., result caching, database-specific tuning)
  • Extensive database/warehouse support via built-in and JDBC drivers

Use Cases

  • Internal analytics portal for product, finance, or operations teams
  • Self-serve reporting for business users on top of PostgreSQL/MySQL and warehouses
  • Embedded analytics inside a customer-facing application

Limitations and Considerations

  • Some advanced governance/embedding capabilities are edition-dependent (open-source vs. paid)
  • Heavy, highly concurrent analytics workloads may require careful database tuning and caching strategy

Metabase is well-suited for teams that want fast time-to-value analytics with both no-code exploration and SQL power. It provides a pragmatic middle ground between lightweight charting tools and heavyweight enterprise BI suites, while remaining deployable on your own infrastructure.

45.5kstars
6.2kforks
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#3
Chartbrew

Chartbrew

Self-hosted dashboard and chart builder that connects to SQL/HTTP data sources, visualizes data with widgets, and supports sharing and embedding dashboards.

Chartbrew screenshot

Chartbrew is an open-source business intelligence (BI) and dashboarding application for building charts and dashboards from multiple data sources. It focuses on quickly creating visual reports, sharing them with teams, and embedding dashboards in other products.

Key Features

  • Connects to multiple data sources (SQL databases and API/HTTP sources) and reuses connections across projects
  • Dashboard builder with configurable chart widgets (multiple chart types) and layout controls
  • Query editor and parameterized queries for dynamic dashboards
  • Team-oriented access control for projects/dashboards and shareable links
  • Embedding options to include charts/dashboards in external web apps
  • Scheduled/automated report delivery and notifications (where configured)
  • Docker-first deployment with environment-based configuration

Use Cases

  • Internal KPI dashboards for product, operations, and finance teams
  • Customer-facing analytics embedded inside a SaaS admin portal
  • Lightweight BI reporting on top of PostgreSQL/MySQL plus API-based metrics

Limitations and Considerations

  • Feature depth is generally lighter than large enterprise BI suites (advanced semantic modeling/governance may be limited)
  • Data-source capabilities depend on the connector type and the underlying database/API

Chartbrew is a practical option for organizations that need a self-managed dashboard layer and embeddable analytics without adopting a full enterprise BI stack. It combines common BI essentials—connectors, charting, sharing, and automation—into a deployable open-source package.

3.5kstars
402forks
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Why choose an open source alternative?

  • •Data ownership: Keep your data on your own servers
  • •No vendor lock-in: Freedom to switch or modify at any time
  • •Cost savings: Reduce or eliminate subscription fees
  • •Transparency: Audit the code and know exactly what's running