Alternatives to Amazon Quicksight logo

Alternatives to Amazon Quicksight

Tableau, DOMO, Looker, Power BI, and Amazon Athena are the most popular alternatives and competitors to Amazon Quicksight.
143
296
+ 1
1

What is Amazon Quicksight and what are its top alternatives?

Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.
Amazon Quicksight is a tool in the Business Intelligence category of a tech stack.

Top Alternatives to Amazon Quicksight

  • 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. ...

  • 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. ...

  • 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. ...

  • 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. ...

  • Amazon Athena

    Amazon Athena

    Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run. ...

  • Kibana

    Kibana

    Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch. ...

  • 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. ...

  • Qlik Sense

    Qlik Sense

    It helps uncover insights that query-based BI tools simply miss. Our one-of-a-kind Associative Engine brings together all your data so users can freely search and explore to find new connections. AI and cognitive capabilities offer insight suggestions, automation and conversational interaction. ...

Amazon Quicksight alternatives & related posts

Tableau logo

Tableau

917
954
5
Tableau helps people see and understand data.
917
954
+ 1
5
PROS OF TABLEAU
  • 4
    Capable of visualising billions of rows
  • 1
    Responsive
CONS OF TABLEAU
    Be the first to leave a con

    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
    DOMO logo

    DOMO

    35
    51
    0
    Domo optimizes your business by connecting you to the data, people, and expertise you need to improve business...
    35
    51
    + 1
    0
    PROS OF DOMO
      Be the first to leave a pro
      CONS OF DOMO
        Be the first to leave a con

        related DOMO posts

        Looker logo

        Looker

        410
        456
        9
        Pioneering the next generation of BI, data discovery & data analytics
        410
        456
        + 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
        • 1
          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
        Power BI logo

        Power BI

        552
        533
        7
        Empower team members to discover insights hidden in your data
        552
        533
        + 1
        7
        PROS OF POWER BI
        • 7
          Cross-filtering
        CONS OF POWER BI
          Be the first to leave a con

          related Power BI 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
          Amazon Athena logo

          Amazon Athena

          387
          615
          46
          Query S3 Using SQL
          387
          615
          + 1
          46
          PROS OF AMAZON ATHENA
          • 15
            Use SQL to analyze CSV files
          • 8
            Glue crawlers gives easy Data catalogue
          • 6
            Cheap
          • 5
            Query all my data without running servers 24x7
          • 4
            No data base servers yay
          • 3
            Easy integration with QuickSight
          • 2
            Query and analyse CSV,parquet,json files in sql
          • 2
            Also glue and athena use same data catalog
          • 1
            No configuration required
          • 0
            Ad hoc checks on data made easy
          CONS OF AMAZON ATHENA
            Be the first to leave a con

            related Amazon Athena posts

            I use Amazon Athena because similar to Google BigQuery , you can store and query data easily. Especially since you can define data schema in the Glue data catalog, there's a central way to define data models.

            However, I would not recommend for batch jobs. I typically use this to check intermediary datasets in data engineering workloads. It's good for getting a look and feel of the data along its ETL journey.

            See more

            Hi all,

            Currently, we need to ingest the data from Amazon S3 to DB either Amazon Athena or Amazon Redshift. But the problem with the data is, it is in .PSV (pipe separated values) format and the size is also above 200 GB. The query performance of the timeout in Athena/Redshift is not up to the mark, too slow while compared to Google BigQuery. How would I optimize the performance and query result time? Can anyone please help me out?

            See more
            Kibana logo

            Kibana

            15K
            11.6K
            255
            Visualize your Elasticsearch data and navigate the Elastic Stack
            15K
            11.6K
            + 1
            255
            PROS OF KIBANA
            • 88
              Easy to setup
            • 61
              Free
            • 44
              Can search text
            • 21
              Has pie chart
            • 13
              X-axis is not restricted to timestamp
            • 8
              Easy queries and is a good way to view logs
            • 6
              Supports Plugins
            • 3
              More "user-friendly"
            • 3
              Can build dashboards
            • 3
              Dev Tools
            • 2
              Easy to drill-down
            • 2
              Out-of-Box Dashboards/Analytics for Metrics/Heartbeat
            • 1
              Up and running
            CONS OF KIBANA
            • 5
              Unintuituve
            • 3
              Elasticsearch is huge
            • 3
              Works on top of elastic only
            • 2
              Hardweight UI

            related Kibana posts

            Tymoteusz Paul
            Devops guy at X20X Development LTD · | 23 upvotes · 4.7M views

            Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

            It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

            I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

            We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

            If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

            The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

            Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

            See more
            Patrick Sun
            Software Engineer at Stitch Fix · | 11 upvotes · 469.6K views

            Elasticsearch's built-in visualization tool, Kibana, is robust and the appropriate tool in many cases. However, it is geared specifically towards log exploration and time-series data, and we felt that its steep learning curve would impede adoption rate among data scientists accustomed to writing SQL. The solution was to create something that would replicate some of Kibana's essential functionality while hiding Elasticsearch's complexity behind SQL-esque labels and terminology ("table" instead of "index", "group by" instead of "sub-aggregation") in the UI.

            Elasticsearch's API is really well-suited for aggregating time-series data, indexing arbitrary data without defining a schema, and creating dashboards. For the purpose of a data exploration backend, Elasticsearch fits the bill really well. Users can send an HTTP request with aggregations and sub-aggregations to an index with millions of documents and get a response within seconds, thus allowing them to rapidly iterate through their data.

            See more
            QlikView logo

            QlikView

            59
            46
            0
            A Business Intelligence platform for turning data into knowledge
            59
            46
            + 1
            0
            PROS OF QLIKVIEW
              Be the first to leave a pro
              CONS OF QLIKVIEW
                Be the first to leave a con

                related QlikView posts

                Qlik Sense logo

                Qlik Sense

                96
                73
                0
                A business intelligence and visual analytics platform
                96
                73
                + 1
                0
                PROS OF QLIK SENSE
                  Be the first to leave a pro
                  CONS OF QLIK SENSE
                    Be the first to leave a con

                    related Qlik Sense posts