Alternatives to Power BI logo

Alternatives to Power BI

DOMO, QlikView, Tableau, Looker, and Metabase are the most popular alternatives and competitors to Power BI.
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What is Power BI and what are its top alternatives?

It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.
Power BI is a tool in the Business Intelligence category of a tech stack.

Top Alternatives to Power BI

  • DOMO
    DOMO

    Domo: business intelligence, data visualization, dashboards and reporting all together. Simplify your big data and improve your business with Domo's agile and mobile-ready platform. ...

  • QlikView
    QlikView

    It is a business discovery platform that provides self-service BI for all business users in organizations. With this tool, you can analyze data and use your data discoveries to support decision making. ...

  • Tableau
    Tableau

    Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click. ...

  • Looker
    Looker

    We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way. ...

  • Metabase
    Metabase

    It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating. ...

  • Metabase
    Metabase

    It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating. ...

  • Data Studio
    Data Studio

    Unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions. It’s easy and free. ...

  • Superset
    Superset

    Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought. ...

Power BI alternatives & related posts

DOMO logo

DOMO

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Domo optimizes your business by connecting you to the data, people, and expertise you need to improve business...
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PROS OF DOMO
    Be the first to leave a pro
    CONS OF DOMO
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      related DOMO posts

      QlikView logo

      QlikView

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      49
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      A Business Intelligence platform for turning data into knowledge
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      49
      + 1
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      PROS OF QLIKVIEW
        Be the first to leave a pro
        CONS OF QLIKVIEW
          Be the first to leave a con

          related QlikView posts

          Tableau logo

          Tableau

          1K
          1.1K
          6
          Tableau helps people see and understand data.
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          PROS OF TABLEAU
          • 4
            Capable of visualising billions of rows
          • 1
            Intuitive and easy to learn
          • 1
            Responsive
          CONS OF TABLEAU
          • 1
            Very expensive for small companies

          related Tableau posts

          Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.

          See more
          Looker logo

          Looker

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          Pioneering the next generation of BI, data discovery & data analytics
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          508
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          PROS OF LOOKER
          • 4
            Real time in app customer chat support
          • 4
            GitHub integration
          • 1
            Reduces the barrier of entry to utilizing data
          CONS OF LOOKER
          • 2
            Price

          related Looker posts

          Mohan Ramanujam

          We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.

          See more
          Metabase logo

          Metabase

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          An open-source business intelligence tool
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          PROS OF METABASE
          • 55
            Database visualisation
          • 41
            Open Source
          • 39
            Easy setup
          • 34
            Dashboard out of the box
          • 19
            Free
          • 13
            Simple
          • 8
            Support for many dbs
          • 7
            Easy embedding
          • 6
            Easy
          • 6
            It's good
          • 5
            AGPL : wont help with adoption but depends on your goal
          • 5
            BI doesn't get easier than that
          • 4
            Multiple integrations
          • 4
            Google analytics integration
          • 3
            Easy set up
          CONS OF METABASE
          • 5
            Harder to setup than similar tools

          related Metabase posts

          Metabase logo

          Metabase

          748
          1K
          249
          An open-source business intelligence tool
          748
          1K
          + 1
          249
          PROS OF METABASE
          • 55
            Database visualisation
          • 41
            Open Source
          • 39
            Easy setup
          • 34
            Dashboard out of the box
          • 19
            Free
          • 13
            Simple
          • 8
            Support for many dbs
          • 7
            Easy embedding
          • 6
            Easy
          • 6
            It's good
          • 5
            AGPL : wont help with adoption but depends on your goal
          • 5
            BI doesn't get easier than that
          • 4
            Multiple integrations
          • 4
            Google analytics integration
          • 3
            Easy set up
          CONS OF METABASE
          • 5
            Harder to setup than similar tools

          related Metabase posts

          Data Studio logo

          Data Studio

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          Your data is powerful. Use it
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          PROS OF DATA STUDIO
            Be the first to leave a pro
            CONS OF DATA STUDIO
              Be the first to leave a con

              related Data Studio posts

              Mohan Ramanujam

              We are a consumer mobile app IOS/Android startup. The app is instrumented with branch and Firebase. We use Google BigQuery. We are looking at tools that can support engagement and cohort analysis at an early stage price which we can grow with. Data Studio is the default but it would seem Looker provides more power. We don't have much insight into Amplitude other than the fact it is a popular PM tool. Please provide some insight.

              See more
              Superset logo

              Superset

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              Data exploration and visualization platform, by Airbnb
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              PROS OF SUPERSET
              • 9
                Awesome interactive filtering
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                Wide SQL database support
              • 6
                Free
              • 6
                Shareable & editable dashboards
              • 5
                Great for data collaborating on data exploration
              • 3
                User & Role Management
              • 3
                Easy to share charts & dasboards
              CONS OF SUPERSET
              • 3
                Link diff db together "Data Modeling "
              • 3
                It is difficult to install on the server
              • 3
                Ugly GUI

              related Superset posts

              Julien DeFrance
              Principal Software Engineer at Tophatter · | 16 upvotes · 2.5M views

              Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

              I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

              For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

              Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

              Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

              Future improvements / technology decisions included:

              Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

              As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

              One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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