Alternatives to Mode logo

Alternatives to Mode

MEAN, Marvel, Hibernate, Metabase, and Tableau are the most popular alternatives and competitors to Mode.
68
61
+ 1
11

What is Mode and what are its top alternatives?

Created by analysts, for analysts, Mode is a SQL-based analytics tool that connects directly to your database. Mode is designed to alleviate the bottlenecks in today's analytical workflow and drive collaboration around data projects.
Mode is a tool in the Business Intelligence category of a tech stack.

Mode alternatives & related posts

MEAN logo

MEAN

312
359
590
312
359
+ 1
590
A Simple, Scalable and Easy starting point for full stack javascript web development
MEAN logo
MEAN
VS
Mode logo
Mode
Marvel logo

Marvel

137
94
45
137
94
+ 1
45
Prototyping for everyone
Marvel logo
Marvel
VS
Mode logo
Mode
Hibernate logo

Hibernate

667
467
16
667
467
+ 1
16
Idiomatic persistence for Java and relational databases.
Hibernate logo
Hibernate
VS
Mode logo
Mode
Tableau logo

Tableau

258
152
0
258
152
+ 1
0
Tableau helps people see and understand data.
    Be the first to leave a pro
    Tableau logo
    Tableau
    VS
    Mode logo
    Mode
    Looker logo

    Looker

    174
    117
    7
    174
    117
    + 1
    7
    Pioneering the next generation of BI, data discovery & data analytics
    Looker logo
    Looker
    VS
    Mode logo
    Mode
    Data Studio logo

    Data Studio

    171
    136
    0
    171
    136
    + 1
    0
    Your data is powerful. Use it
      Be the first to leave a pro
      Data Studio logo
      Data Studio
      VS
      Mode logo
      Mode
      Redash logo

      Redash

      137
      110
      2
      137
      110
      + 1
      2
      Easily query an existing database, share the dataset and visualize it in different ways
      Redash logo
      Redash
      VS
      Mode logo
      Mode

      related Superset posts

      Julien DeFrance
      Julien DeFrance
      Principal Software Engineer at Tophatter | 16 upvotes 837K views
      atSmartZipSmartZip
      Rails
      Rails
      Rails API
      Rails API
      AWS Elastic Beanstalk
      AWS Elastic Beanstalk
      Capistrano
      Capistrano
      Docker
      Docker
      Amazon S3
      Amazon S3
      Amazon RDS
      Amazon RDS
      MySQL
      MySQL
      Amazon RDS for Aurora
      Amazon RDS for Aurora
      Amazon ElastiCache
      Amazon ElastiCache
      Memcached
      Memcached
      Amazon CloudFront
      Amazon CloudFront
      Segment
      Segment
      Zapier
      Zapier
      Amazon Redshift
      Amazon Redshift
      Amazon Quicksight
      Amazon Quicksight
      Superset
      Superset
      Elasticsearch
      Elasticsearch
      Amazon Elasticsearch Service
      Amazon Elasticsearch Service
      New Relic
      New Relic
      AWS Lambda
      AWS Lambda
      Node.js
      Node.js
      Ruby
      Ruby
      Amazon DynamoDB
      Amazon DynamoDB
      Algolia
      Algolia

      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
      Power BI logo

      Power BI

      75
      61
      0
      75
      61
      + 1
      0
      A business analytics service
        Be the first to leave a pro
        Power BI logo
        Power BI
        VS
        Mode logo
        Mode
        Chartio logo

        Chartio

        44
        33
        6
        44
        33
        + 1
        6
        A powerful Business Intelligence tool anyone can use
        Chartio logo
        Chartio
        VS
        Mode logo
        Mode
        Amazon Quicksight logo

        Amazon Quicksight

        42
        52
        1
        42
        52
        + 1
        1
        Fast, easy to use business analytics at 1/10th the cost of traditional BI solutions
        Amazon Quicksight logo
        Amazon Quicksight
        VS
        Mode logo
        Mode

        related Amazon Quicksight posts

        Julien DeFrance
        Julien DeFrance
        Principal Software Engineer at Tophatter | 16 upvotes 837K views
        atSmartZipSmartZip
        Rails
        Rails
        Rails API
        Rails API
        AWS Elastic Beanstalk
        AWS Elastic Beanstalk
        Capistrano
        Capistrano
        Docker
        Docker
        Amazon S3
        Amazon S3
        Amazon RDS
        Amazon RDS
        MySQL
        MySQL
        Amazon RDS for Aurora
        Amazon RDS for Aurora
        Amazon ElastiCache
        Amazon ElastiCache
        Memcached
        Memcached
        Amazon CloudFront
        Amazon CloudFront
        Segment
        Segment
        Zapier
        Zapier
        Amazon Redshift
        Amazon Redshift
        Amazon Quicksight
        Amazon Quicksight
        Superset
        Superset
        Elasticsearch
        Elasticsearch
        Amazon Elasticsearch Service
        Amazon Elasticsearch Service
        New Relic
        New Relic
        AWS Lambda
        AWS Lambda
        Node.js
        Node.js
        Ruby
        Ruby
        Amazon DynamoDB
        Amazon DynamoDB
        Algolia
        Algolia

        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
        Periscope logo

        Periscope

        41
        44
        9
        41
        44
        + 1
        9
        Periscope plugs directly into your database and lets you run, save and share analyses over billions of data...
        Periscope logo
        Periscope
        VS
        Mode logo
        Mode
        Shiny logo

        Shiny

        41
        23
        0
        41
        23
        + 1
        0
        An R package that makes it easy to build interactive web apps
          Be the first to leave a pro
          Shiny logo
          Shiny
          VS
          Mode logo
          Mode
          Google Datastudio logo

          Google Datastudio

          37
          20
          2
          37
          20
          + 1
          2
          A reporting and data visualization tool
          Google Datastudio logo
          Google Datastudio
          VS
          Mode logo
          Mode
          Microsoft SSRS logo

          Microsoft SSRS

          30
          23
          0
          30
          23
          + 1
          0
          A server-based report generating software system
            Be the first to leave a pro
            Microsoft SSRS logo
            Microsoft SSRS
            VS
            Mode logo
            Mode
            Qlik Sense logo

            Qlik Sense

            23
            8
            0
            23
            8
            + 1
            0
            A business intelligence and visual analytics platform
              Be the first to leave a pro
              Qlik Sense logo
              Qlik Sense
              VS
              Mode logo
              Mode
              QlikView logo

              QlikView

              19
              13
              0
              19
              13
              + 1
              0
              A Business Intelligence platform for turning data into knowledge
                Be the first to leave a pro
                QlikView logo
                QlikView
                VS
                Mode logo
                Mode
                Cube.js logo

                Cube.js

                18
                31
                13
                18
                31
                + 1
                13
                Open Source Analytics Framework
                Cube.js logo
                Cube.js
                VS
                Mode logo
                Mode
                GoodData logo

                GoodData

                17
                18
                0
                17
                18
                + 1
                0
                We help businesses monetize big data.
                  Be the first to leave a pro
                  GoodData logo
                  GoodData
                  VS
                  Mode logo
                  Mode