Alternatives to freeboard logo

Alternatives to freeboard

Grafana, Geckoboard, Google Analytics, Google Tag Manager, and Mixpanel are the most popular alternatives and competitors to freeboard.
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What is freeboard and what are its top alternatives?

Freeboard is a free, open-source platform for creating real-time interactive dashboards. It offers users the ability to connect various data sources, visualize data in different chart formats, and customize the dashboard layout. However, freeboard has limitations in terms of less advanced features compared to some other dashboard tools in the market.

  1. Grafana: Grafana is a popular open-source platform for creating monitoring and dashboarding solutions. Key features include multiple data source support, plugins for extending functionality, and alerting capabilities. Pros include a large community for support and frequent updates, while cons may include a steeper learning curve compared to freeboard.
  2. Tableau Public: Tableau Public is a data visualization tool that allows users to create interactive charts and dashboards. Key features include a drag-and-drop interface, multiple data source connectivity, and sharing capabilities. Pros include ease of use and professional-looking visuals, while cons include limited data source options compared to paid versions.
  3. Google Data Studio: Google Data Studio is a free tool for creating customizable reports and dashboards. Key features include integration with Google products like Analytics and Sheets, collaboration options, and data blending capabilities. Pros include seamless integration with Google services and easy sharing options, while cons may include limited data source connectivity.
  4. Power BI: Power BI is a business analytics tool by Microsoft that allows users to create interactive reports and dashboards. Key features include AI-powered insights, real-time streaming data, and integration with Microsoft products. Pros include advanced analytics capabilities and easy data visualization, while cons may include a paid subscription for some features.
  5. Domo: Domo is a cloud-based business intelligence platform that offers interactive dashboards and data visualization. Key features include predictive analytics, mobile app support, and collaboration tools. Pros include a user-friendly interface and pre-built connectors, while cons may include a higher cost compared to freeboard.
  6. Zoho Analytics: Zoho Analytics is a self-service BI and data analytics software that allows users to create shareable dashboards and reports. Key features include drag-and-drop interface, AI-driven insights, and integration with Zoho applications. Pros include affordable pricing and ease of use, while cons may include limited customization options compared to other tools.
  7. Looker: Looker is a data analytics platform that offers data exploration and visualization capabilities. Key features include SQL-based query language, data modeling tools, and embedded analytics options. Pros include powerful data modeling capabilities and robust security features, while cons may include a steeper learning curve for beginners.
  8. Metabase: Metabase is an open-source data exploration tool that allows users to create charts and dashboards from their databases. Key features include simple querying interface, native support for multiple databases, and sharing options. Pros include easy setup and customization, while cons may include limited advanced analytics features compared to other tools.
  9. Chartio: Chartio is a cloud-based business intelligence platform that offers interactive dashboards and advanced analytics features. Key features include data pipeline for data transformation, visualization customization options, and collaboration tools. Pros include easy data blending and powerful dashboard building capabilities, while cons may include a higher price point compared to freeboard.
  10. Redash: Redash is an open-source data visualization tool that allows users to connect to various data sources and create interactive dashboards. Key features include SQL querying, shareable dashboards, and alerts. Pros include flexibility in data source connectivity and ease of sharing, while cons may include limited customization options compared to some other tools.

Top Alternatives to freeboard

  • Grafana
    Grafana

    Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins. ...

  • Geckoboard
    Geckoboard

    Build and share real-time business dashboards without the hassle. Geckoboard integrates directly with over 80 different tools and services to help you pull in your data and get a professional-looking dashboard in front of others in minutes. ...

  • Google Analytics
    Google Analytics

    Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications. ...

  • Google Tag Manager
    Google Tag Manager

    Tag Manager gives you the ability to add and update your own tags for conversion tracking, site analytics, remarketing, and more. There are nearly endless ways to track user behavior across your sites and apps, and the intuitive design lets you change tags whenever you want. ...

  • Mixpanel
    Mixpanel

    Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...

  • Mixpanel
    Mixpanel

    Mixpanel helps companies build better products through data. With our powerful, self-serve product analytics solution, teams can easily analyze how and why people engage, convert, and retain to improve their user experience. ...

  • Optimizely
    Optimizely

    Optimizely is the market leader in digital experience optimization, helping digital leaders and Fortune 100 companies alike optimize their digital products, commerce, and campaigns with a fully featured experimentation platform. ...

  • Segment
    Segment

    Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch. ...

freeboard alternatives & related posts

Grafana logo

Grafana

17.9K
415
Open source Graphite & InfluxDB Dashboard and Graph Editor
17.9K
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PROS OF GRAFANA
  • 89
    Beautiful
  • 68
    Graphs are interactive
  • 57
    Free
  • 56
    Easy
  • 34
    Nicer than the Graphite web interface
  • 26
    Many integrations
  • 18
    Can build dashboards
  • 10
    Easy to specify time window
  • 10
    Can collaborate on dashboards
  • 9
    Dashboards contain number tiles
  • 5
    Open Source
  • 5
    Integration with InfluxDB
  • 5
    Click and drag to zoom in
  • 4
    Authentification and users management
  • 4
    Threshold limits in graphs
  • 3
    Alerts
  • 3
    It is open to cloud watch and many database
  • 3
    Simple and native support to Prometheus
  • 2
    Great community support
  • 2
    You can use this for development to check memcache
  • 2
    You can visualize real time data to put alerts
  • 0
    Grapsh as code
  • 0
    Plugin visualizationa
CONS OF GRAFANA
  • 1
    No interactive query builder

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Matt Menzenski
Senior Software Engineering Manager at PayIt · | 16 upvotes · 1M views

Grafana and Prometheus together, running on Kubernetes , is a powerful combination. These tools are cloud-native and offer a large community and easy integrations. At PayIt we're using exporting Java application metrics using a Dropwizard metrics exporter, and our Node.js services now use the prom-client npm library to serve metrics.

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Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 15 upvotes · 5M views

Why we spent several years building an open source, large-scale metrics alerting system, M3, built for Prometheus:

By late 2014, all services, infrastructure, and servers at Uber emitted metrics to a Graphite stack that stored them using the Whisper file format in a sharded Carbon cluster. We used Grafana for dashboarding and Nagios for alerting, issuing Graphite threshold checks via source-controlled scripts. While this worked for a while, expanding the Carbon cluster required a manual resharding process and, due to lack of replication, any single node’s disk failure caused permanent loss of its associated metrics. In short, this solution was not able to meet our needs as the company continued to grow.

To ensure the scalability of Uber’s metrics backend, we decided to build out a system that provided fault tolerant metrics ingestion, storage, and querying as a managed platform...

https://eng.uber.com/m3/

(GitHub : https://github.com/m3db/m3)

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Geckoboard logo

Geckoboard

96
7
Create and share professional-looking KPI dashboards that always stay up-to-date. No hassle.
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PROS OF GECKOBOARD
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    Google Analytics logo

    Google Analytics

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    Enterprise-class web analytics.
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    • 927
      Easy setup
    • 891
      Data visualization
    • 698
      Real-time stats
    • 406
      Comprehensive feature set
    • 182
      Goals tracking
    • 155
      Powerful funnel conversion reporting
    • 139
      Customizable reports
    • 83
      Custom events try
    • 53
      Elastic api
    • 15
      Updated regulary
    • 8
      Interactive Documentation
    • 4
      Google play
    • 3
      Walkman music video playlist
    • 3
      Industry Standard
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      Advanced ecommerce
    • 2
      Irina
    • 2
      Easy to integrate
    • 2
      Financial Management Challenges -2015h
    • 2
      Medium / Channel data split
    • 2
      Lifesaver
    CONS OF GOOGLE ANALYTICS
    • 11
      Confusing UX/UI
    • 8
      Super complex
    • 6
      Very hard to build out funnels
    • 4
      Poor web performance metrics
    • 3
      Very easy to confuse the user of the analytics
    • 2
      Time spent on page isn't accurate out of the box

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    Max Musing
    Founder & CEO at BaseDash · | 8 upvotes · 368.6K views

    Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).

    Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.

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    Google Tag Manager logo

    Google Tag Manager

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    Quickly and easily update tags and code snippets on your website or mobile app
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        Iva Obrovac
        Product Marketing Manager at Martian & Machine · | 8 upvotes · 86K views

        Hi,

        This is a question for best practice regarding Segment and Google Tag Manager. I would love to use Segment and GTM together when we need to implement a lot of additional tools, such as Amplitude, Appsfyler, or any other engagement tool since we can send event data without additional SDK implementation, etc.

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        From my point of view, implementing marketing pixels should stay in GTM because of the tag/trigger control.

        If you are using Segment and GTM together, I would love to learn more about your best practice.

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        Mixpanel logo

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          Easy integration
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          Great funnel funcionality
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          Free
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          A wide range of tools
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          Powerful Graph Search
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        Max Musing
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        Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).

        Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.

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        Yasmine de Aranda
        Chief Growth Officer at Huddol · | 7 upvotes · 386.2K views

        Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!

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        Mixpanel logo

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        Powerful, self-serve product analytics to help you convert, engage, and retain more users
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          Easy integration
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          Great funnel funcionality
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          Free
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          A wide range of tools
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          Powerful Graph Search
        • 11
          Responsive Customer Support
        • 2
          Nice reporting
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          Messaging (notification, email) features are weak
        • 2
          Paid plans can get expensive
        • 1
          Limited dashboard capabilities

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        Max Musing
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        Functionally, Amplitude and Mixpanel are incredibly similar. They both offer almost all the same functionality around tracking and visualizing user actions for analytics. You can track A/B test results in both. We ended up going with Amplitude at BaseDash because it has a more generous free tier for our uses (10 million actions per month, versus Mixpanel's 1000 monthly tracked users).

        Segment isn't meant to compete with these tools, but instead acts as an API to send actions to them, and other analytics tools. If you're just sending event data to one of these tools, you probably don't need Segment. If you're using other analytics tools like Google Analytics and FullStory, Segment makes it easy to send events to all your tools at once.

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        Yasmine de Aranda
        Chief Growth Officer at Huddol · | 7 upvotes · 386.2K views

        Hi there, we are a seed-stage startup in the personal development space. I am looking at building the marketing stack tool to have an accurate view of the user experience from acquisition through to adoption and retention for our upcoming React Native Mobile app. We qualify for the startup program of Segment and Mixpanel, which seems like a good option to get rolling and scale for free to learn how our current 60K free members will interact in the new subscription-based platform. I was considering AppsFlyer for attribution, and I am now looking at an affordable yet scalable Mobile Marketing tool vs. building in-house. Braze looks great, so does Leanplum, but the price points are 30K to start, which we can't do. I looked at OneSignal, but it doesn't have user flow visualization. I am now looking into Urban Airship and Iterable. Any advice would be much appreciated!

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        Optimizely logo

        Optimizely

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          Hey all, I'm managing the implementation of a customer data platform and headless CMS for a digital consumer content publisher. We're weighing up the pros and cons of implementing an OTB activation platform like Optimizely Recommendations or Dynamic Yield vs developing a bespoke solution for personalising content recommendations. Use Case is CDP will house customers and personas, and headless CMS will contain the individual content assets. The intermediary solution will activate data between the two for personalisation of news content feeds. I saw GCP has some potentially applicable personalisation solutions such as recommendations AI, which seem to be targeted at retail, but would probably be relevant to this use case for all intents and purposes. The CDP is Segment and the CMS is Contentstack. Has anyone implemented an activation platform or personalisation solution under similar circumstances? Any advice or direction would be appreciated! Thank you

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          Segment logo

          Segment

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          A single hub to collect, translate and send your data with the flip of a switch.
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            One API
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            Simple
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            Multiple integrations
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            Cleanest API
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            Easy
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            Free
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            Mixpanel Integration
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            Segment SQL
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            Flexible
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            Google Analytics Integration
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            Salesforce Integration
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            SQL Access
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            Clean Integration with Application
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            Own all your tracking data
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            Quick setup
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            Clearbit integration
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            Beautiful UI
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            Limitations with integration-specific configurations
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            Client-side events are separated from server-side

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          Principal Software Engineer at Tophatter · | 16 upvotes · 3.2M 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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          Robert Zuber

          Our primary source of monitoring and alerting is Datadog. We’ve got prebuilt dashboards for every scenario and integration with PagerDuty to manage routing any alerts. We’ve definitely scaled past the point where managing dashboards is easy, but we haven’t had time to invest in using features like Anomaly Detection. We’ve started using Honeycomb for some targeted debugging of complex production issues and we are liking what we’ve seen. We capture any unhandled exceptions with Rollbar and, if we realize one will keep happening, we quickly convert the metrics to point back to Datadog, to keep Rollbar as clean as possible.

          We use Segment to consolidate all of our trackers, the most important of which goes to Amplitude to analyze user patterns. However, if we need a more consolidated view, we push all of our data to our own data warehouse running PostgreSQL; this is available for analytics and dashboard creation through Looker.

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