Alternatives to Cumul.io logo

Alternatives to Cumul.io

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

Create powerful dashboards in minutes. Share with your teams, or integrate in your platform. Drive growth in your business today! Designing great graphs quick, like Klipfolio, but easier. Many datasource plugins
Cumul.io is a tool in the Business Dashboards category of a tech stack.

Top Alternatives to Cumul.io

  • 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. ...

  • 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. ...

  • Power BI

    Power BI

    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. ...

  • 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. ...

  • Data Studio

    Data Studio

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

  • Redash

    Redash

    Redash helps you make sense of your data. Connect and query your data sources, build dashboards to visualize data and share them with your company. ...

  • 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. ...

Cumul.io alternatives & related posts

Tableau logo

Tableau

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832
2
Tableau helps people see and understand data.
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+ 1
2
PROS OF TABLEAU
  • 1
    Responsive
  • 1
    Capable of visualising billions of rows
CONS OF TABLEAU
    Be the first to leave a con

    related Tableau posts

    Metabase logo

    Metabase

    588
    841
    237
    An open-source business intelligence tool
    588
    841
    + 1
    237
    PROS OF METABASE
    • 51
      Database visualisation
    • 41
      Open Source
    • 38
      Easy setup
    • 32
      Dashboard out of the box
    • 17
      Free
    • 12
      Simple
    • 8
      Support for many dbs
    • 7
      Easy embedding
    • 6
      It's good
    • 6
      Easy
    • 5
      AGPL : wont help with adoption but depends on your goal
    • 5
      BI doesn't get easier than that
    • 4
      Multiple integrations
    • 3
      Easy set up
    • 2
      Google analytics integration
    CONS OF METABASE
    • 3
      Harder to setup than similar tools

    related Metabase posts

    Metabase logo

    Metabase

    588
    841
    237
    An open-source business intelligence tool
    588
    841
    + 1
    237
    PROS OF METABASE
    • 51
      Database visualisation
    • 41
      Open Source
    • 38
      Easy setup
    • 32
      Dashboard out of the box
    • 17
      Free
    • 12
      Simple
    • 8
      Support for many dbs
    • 7
      Easy embedding
    • 6
      It's good
    • 6
      Easy
    • 5
      AGPL : wont help with adoption but depends on your goal
    • 5
      BI doesn't get easier than that
    • 4
      Multiple integrations
    • 3
      Easy set up
    • 2
      Google analytics integration
    CONS OF METABASE
    • 3
      Harder to setup than similar tools

    related Metabase posts

    Power BI logo

    Power BI

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    5
    A business analytics service
    456
    441
    + 1
    5
    PROS OF POWER BI
    • 5
      Cross-filtering
    CONS OF POWER BI
      Be the first to leave a con

      related Power BI posts

      Looker logo

      Looker

      361
      400
      9
      Pioneering the next generation of BI, data discovery & data analytics
      361
      400
      + 1
      9
      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
        Be the first to leave a con

        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
        Data Studio logo

        Data Studio

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        227
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        Your data is powerful. Use it
        277
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        + 1
        0
        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
            Redash logo

            Redash

            261
            348
            6
            Easily query an existing database, share the dataset and visualize it in different ways
            261
            348
            + 1
            6
            PROS OF REDASH
            • 3
              Open Source
            • 3
              SQL Friendly
            CONS OF REDASH
            • 1
              All results are loaded into RAM before displaying
            • 1
              Memory Leaks

            related Redash posts

            Superset logo

            Superset

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            613
            30
            Data exploration and visualization platform, by Airbnb
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            30
            PROS OF SUPERSET
            • 8
              Awesome interactive filtering
            • 6
              Wide SQL database support
            • 5
              Shareable & editable dashboards
            • 4
              Free
            • 3
              Easy to share charts & dasboards
            • 2
              User & Role Management
            • 2
              Great for data collaborating on data exploration
            CONS OF SUPERSET
            • 3
              Ugly GUI
            • 2
              It is difficult to install on the server
            • 2
              Link diff db together "Data Modeling "

            related Superset posts

            Julien DeFrance
            Principal Software Engineer at Tophatter | 16 upvotes 路 2.3M 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.

            See more