Power BI Alternative: Finding the Best Fit for Your Business

Power BI Alternative: Finding the Best Fit for Your Business

Power BI Alternative: Finding the Best Fit for Your Business

In the analytics and BI market, a range of solutions cater to diverse business needs. These requirements include self-service options, high performance with large datasets, efficient change management, extensive customization, and AI-enhanced capabilities. Both GoodData and Power BI offer unique approaches to meet these demands — in this article, we compare them directly. For more information on choosing a BI solution, check out our other guides: How to Evaluate BI Tools to Choose the Best One and Comparing the Best BI Tools: Select the Right Solution for Your Business.

What is GoodData?

GoodData is a cloud-based analytics platform that enables users to build highly scalable and easily governed data products. It offers various analytics solutions, from dashboards to API integrations, providing the seamless embedding of analytics into applications for personalized user experiences and strategic business decisions.

What makes GoodData stand out?

  • Ensures scalability and governance by centralizing metrics within the semantic layer, maintaining data integrity and consistency.
  • Facilitates easy provisioning of new interfaces and centralized updates via the inheritance model.
  • Offers a fully customizable interface with white-labeling, flexible embedding, and intuitive navigation to enhance the user experience.
  • Supports diverse user needs with no-code, low-code, and full-code options.
  • Encourages collaboration with an easy-to-use interface, AI features, and enables extensive customization through its "as code" approach.

GoodData dashboard example

Example of a dashboard in GoodData

What is Power BI?

Power BI is a business analytics service developed by Microsoft that provides interactive visualizations and business intelligence capabilities. Unfortunately, Power BI offers so many options that the interface is not as simple as it used to be, which makes it challenging for end users to create reports and dashboards. Power BI comprises several products that work together:

  • Power BI Desktop: A free application for creating data models, dashboards, and reports on your computer.
  • Power BI Service: A cloud-based platform for publishing, sharing, and collaborating on reports and dashboards.
  • Power BI Mobile: An app for accessing Power BI content on mobile devices.
  • Power BI Embedded: A product for integrating Power BI visualizations and reports into user apps.
  • Power BI Report Server: An on-premises solution for managing and publishing reports on your servers.

What is Power BI well-known for?

  • Microsoft integration: Seamlessly integrates with Azure, SQL Server, and Excel, and is supported by a large user community.
  • High number of visualizations: Offers various types of out-of-the-box visualizations, but some require additional settings
  • Robust data connectivity: Connects to numerous data sources, supporting real-time monitoring for timely decisions.
Dashboard example in Power BI

Power BI dashboard example (resource: Introduction to dashboards)

Key differences between GoodData and Power BI

Power BI and GoodData are strong cloud-based competitors in the BI market and offer comprehensive solutions for various industries. Let’s examine how the two tools compare across different features.


  • GoodData offers flexible deployment across AWS, Azure, and Google Cloud, your own cloud, or hybrid approaches. Its microservice-based architecture seamlessly integrates with existing infrastructure, enabling scalable analytics for employees, customers, and partners. Leveraging Headless BI, GoodData integrates with modern tools for data pipelines, applications, AI/ML tools, and other BI platforms through robust API integrations, fitting well into modern data stacks and supporting diverse tools and platforms.

  • With Power BI, users are primarily tied to the Azure ecosystem, lacking a hybrid option. Users who want to host on-premises are limited to using Power BI Report Server, which offers fewer features than its cloud counterpart.

Data integration

  • GoodData manages data integration by supporting various data sources using pre-built connectors. Organizations can connect non-supported databases using Apache Drill or Dremio, making it a flexible and user-friendly platform. GoodData easily integrates with external ETL tools such as Meltano and dbt, which are ideal for managing complex and modern data stacks. It also offers various blueprints, such as Data Pipelines as Code, to streamline data integration and enhance connectivity to the platform.​

  • Power BI integrates with numerous data sources using built-in connectors for SQL databases, Azure services, web APIs, and third-party applications like Salesforce or Google Analytics. Microsoft offers various ETL tools to streamline data integration. Microsoft Fabric further enhances this integration by providing a unified data environment, leveraging OneLake for centralized storage, and supporting open data formats for seamless operations across different workloads​.

Data modeling

Both alternatives, GoodData and Power BI, employ logical data models (LDMs). GoodData uses the LDM Modeler and SQL adjustments via Last Mile ETL, without impacting the data warehouse. Power BI uses Power Query for data model changes, including filtering, merging, and aggregating data, but it has a steeper learning curve.

Semantic layer

Both platforms have a semantic layer, a logical layer between the database and presentation layer that contains the transformations, calculations, metrics, and data relationships needed to create reports and dashboards.

  • GoodData offers a flexible and scalable semantic layer that supports complex integrations and unified governance. This layer is ideal for advanced data management across various tools and platforms. It is central to GoodData's Headless BI architecture and enables easy integration with front-end tools through APIs.

  • Power BI emphasizes an integrated approach with user-friendly tools for business users. This facilitates the easy creation and sharing of consistent data models within the Microsoft ecosystem.

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  • GoodData enhances data processing with FlexCache, which stores pre-aggregated calculations used in dashboards. Built on Apache Arrow, its columnar format boosts performance, scalability, and cost-effectiveness, reducing data storage costs and efficiently managing data growth for easy scalability.

  • Power BI can be slow with extensive datasets. While good performance is achievable with OneLake (part of Microsoft Fabric), it will require additional capacity and storage fees within the broader Azure architecture. However, OneLake — Microsoft Fabric's key feature — enhances query performance by loading Delta-Parquet files directly from OneLake without data duplication.


Both competitors leverage multi-tenant architecture and offer scalable analytics solutions with shared infrastructure, isolated workspaces, and centralized tenant administration and permission management tools.

  • GoodData supports automated scaling and change management, allowing updates without breaking customizations. Tenants can customize environments with unique settings and branding. GoodData’s self-service capabilities allow individuals to create metrics, visualizations, and dashboards, reducing reliance on other teams.

  • Power BI mainly offers self-service to authors who create and publish content. Users need more interactivity and often request additional reports for deeper analysis. At scale, organizations typically need extra tools and frameworks for managing administration, performance, data integrity, and system interoperability.


Both competitors offer embedding options — from basic iFrames to advanced SDKs. Power BI is not API-first, limiting some capabilities in its SDKs. Compared to Power BI’s limited customization capabilities, GoodData offers far more flexibility and customization — it supports embedding via React SDK or Web Components. For a more detailed comparison of how different solutions approach embedding, check out our e-book: The Best Embedded Analytics Tools: A Detailed Comparison Guide.

Developer experience

  • GoodData's "analytics as code" framework integrates with modern DevOps practices, supporting version control systems and simplifying testing and deployment with its VS Code Extension. Its API-first design facilitates CI/CD pipeline integration for systematic updates and automation. GoodData also offers GitHub integration, enabling you to manage your analytics code just like you would with software codebases. This enhances collaboration and consistency and provides blueprints for quick and easy customer onboarding.

  • Power BI improves the developer experience with deployment pipelines for promoting content across environments, Azure DevOps integration for automated deployments, and Git integration for version control of .pbix files. The ALM Toolkit simplifies the versioning, branching, and merging of Power BI assets, supporting effective change management and collaboration.

AI-enhanced analytics

  • GoodData leverages an open-source approach; it uses analytics as code and FlexQuery to integrate AI features using large language models. Through a semantic layer, GoodData simplifies technical terms for non-technical users This layer also enhances AI capabilities (e.g., AI chat assistants, visualization explanations, machine learning in dashboards, and predictive analytics) by supporting public models like OpenAI's ChatGPT 4.0.

  • Power BI integrates AI tools like Co-Pilot for chatbot assistance and Quick Insights and Q&A for natural language queries. However, these features must be manually added to dashboards. AutoML capabilities require Azure Machine Learning, incurring extra costs and necessitating integration with the broader Microsoft ecosystem. Microsoft Fabric enhances the platform with advanced AI/ML capabilities, including built-in AI features from Azure OpenAI Service for creating dataflows, generating code, building machine learning models, and visualizing results.


  • GoodData's pricing model is transparent and straightforward, ensuring cost predictability in B2B settings. It charges based on user adoption for internal usage scenarios and offers specific tiers for startups. For external usage (i.e., customer monetization), it employs a per-workspace model, where each vendor, partner, or client receives a designated workspace. This flexible pricing accommodates various budgets and use cases, with no limitations on user access per workspace, making it ideal for B2B analytics products.

  • Power BI's pricing model is flexible but can be complex and non-transparent, which makes it difficult to predict future usage costs. It charges per user for individual use or per capacity for large-scale deployments. For Power BI Embedded, costs depend on the type and number of nodes, allowing developers to scale based on usage. However, additional charges may apply when integrating with other Microsoft services.

Why choose GoodData over Power BI?

  • Simplicity: Intuitive interface makes data management and analysis easy through no-code UI and AI-enhanced features.
  • Flexibility: GoodData offers flexible deployment across major cloud platforms like AWS, Azure, and Google Cloud, integrating seamlessly with existing infrastructures and tools.
  • Productivity: Efficiency is maximized through automation, collaboration, and governance, leveraging everything as code.
  • Scalability: GoodData supports automated scaling and advanced data management for performance and cost-effectiveness as the data and user base grow.

Next steps with GoodData

Still deciding whether to choose GoodData or Power BI? Experience GoodData for yourself with a free trial. Alternatively, request a demo for a personalized platform walkthrough.

Find out how we stack up against our other competitors

Check out the resources below to discover how we compare to other GoodData alternatives:

AWS QuickSight Alternative: Choosing the Right BI Tool for Your Needs

Sisense Alternative: Elevate Your Analytics Game with Dynamic Solutions

Tableau Alternative: Addressing Challenges and Solutions for Modern Analytics

Qlik Alternative: Which Tool is Better for Your Analytics?

Domo Alternative: Discover the Right BI Tool for Your Needs

Looker Alternative: Which BI Tool Better Fits Your Business Needs?

Note: The above evaluation of features is based on our best understanding of publicly available information available at the time of publishing (Jun ‘24). To understand more specific details and feature differences, readers are encouraged to perform their own research. All of the product names, logos, and brands used are for identification purposes only and remain the property of their respective owners. Use of them does not imply any affiliation with or endorsement by them.

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