Superset vs Tableau

Overview

Tableau

Stacks1.3K

Followers1.4K

Votes8

Superset

Stacks420

Followers1.0K

Votes45

Superset vs Tableau: What are the differences?

Comparison between Superset and Tableau

Superset and Tableau are both powerful data visualization tools, but they have some key differences. Here are six specific differences between the two:

User Interface: Superset offers a web-based user interface that is highly customizable and allows for interactive exploration of data. Tableau, on the other hand, provides a more user-friendly drag-and-drop interface that is suitable for users with less technical expertise.
Data Sources: While Tableau supports a wide range of data sources, including databases, spreadsheets, and cloud services, Superset has native support for SQL databases only. This means that Superset may be more suitable for organizations that primarily work with SQL databases.
Integration: Tableau offers seamless integration with various data management and analytics platforms, such as Salesforce and Hadoop, allowing users to easily import and analyze data from these sources. Superset, on the other hand, lacks such extensive integration capabilities, making it less suitable for organizations with diverse data sources.
Pricing Model: Tableau follows a subscription-based pricing model, which can be costly for organizations that require multiple licenses. In contrast, Superset is an open-source tool, meaning that it is free to use and can be customized as per the organization's needs.
Community Support: Tableau has a large and active user community, with extensive documentation, forums, and knowledge-sharing platforms, making it easier for users to find support and solutions to their problems. Superset, being a relatively newer tool, has a smaller community, which may limit the availability of resources for users seeking assistance.
Advanced Analytics: Tableau offers a wide range of advanced analytics features, including predictive modeling, statistical analysis, and data blending, enabling users to gain deeper insights from their data. Superset, on the other hand, focuses mainly on data visualization and lacks some of the advanced analytics capabilities offered by Tableau.

In summary, Superset and Tableau differ in terms of user interface, supported data sources, integration capabilities, pricing model, community support, and advanced analytics features. Choosing the right tool depends on the specific needs and requirements of the organization.

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Advice on Tableau, Superset

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

353k views353k

Comments

Wei

CTO at Flux Work

Jan 8, 2020

Decided

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

230k views230k

Comments

Detailed Comparison

Tableau	Superset
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.	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.
Connect to data on prem or in the cloud—whether it’s big data, a SQL database, a spreadsheet, or cloud apps like Google Analytics and Salesforce. Access and combine disparate data without writing code. Power users can pivot, split, and manage metadata to optimize data sources. Analysis begins with data. Get more from yours with Tableau.; Exceptional analytics demand more than a pretty dashboard. Quickly build powerful calculations from existing data, drag and drop reference lines and forecasts, and review statistical summaries. Make your point with trend analyses, regressions, and correlations for tried and true statistical understanding. Ask new questions, spot trends, identify opportunities, and make data-driven decisions with confidence.; Answer the “where” as well as the “why.” Create interactive maps automatically. Built-in postal codes mean lightning-fast mapping for more than 50 countries worldwide. Use custom geocodes and territories for personalized regions, like sales areas. We designed Tableau maps specifically to help your data stand out.; Ditch the static slides for live stories that others can explore. Create a compelling narrative that empowers everyone you work with to ask their own questions, analyzing interactive visualizations with fresh data. Be part of a culture of data collaboration, extending the impact of your insights.	A rich set of visualizations to analyze your data, as well as a flexible way to extend the capabilities;An extensible, high granularity security model allowing intricate rules on who can access which features, and integration with major authentication providers (database, OpenID, LDAP, OAuth & REMOTE_USER through Flask AppBuiler);A simple semantic layer, allowing to control how data sources are displayed in the UI, by defining which fields should show up in which dropdown and which aggregation and function (metrics) are made available to the user;Deep integration with Druid allows for Caravel to stay blazing fast while slicing and dicing large, realtime datasets;
Statistics
Stacks 1.3K	Stacks 420
Followers 1.4K	Followers 1.0K
Votes 8	Votes 45
Pros & Cons
Pros 6 Capable of visualising billions of rows 1 Intuitive and easy to learn 1 Responsive Cons 3 Very expensive for small companies	Pros 13 Awesome interactive filtering 9 Free 6 Shareable & editable dashboards 6 Wide SQL database support 5 Great for data collaborating on data exploration Cons 4 Link diff db together "Data Modeling " 3 Ugly GUI 3 It is difficult to install on the server

What are some alternatives to Tableau, Superset?

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.

Cube

Cube: the universal semantic layer that makes it easy to connect BI silos, embed analytics, and power your data apps and AI with context.

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.

Mode

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.

Google Datastudio

It lets you create reports and data visualizations. Data Sources are reusable components that connect a report to your data, such as Google Analytics, Google Sheets, Google AdWords and so forth. You can unlock the power of your data with interactive dashboards and engaging reports that inspire smarter business decisions.

AskNed

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

It is an open source R package that provides an elegant and powerful web framework for building web applications using R. It helps you turn your analyses into interactive web applications without requiring HTML, CSS, or JavaScript knowledge.

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.

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Periscope

Periscope is a data analysis tool that uses pre-emptive in-memory caching and statistical sampling to run data analyses really, really fast.

Related Comparisons

Superset vs Tableau: What are the differences?

Comparison between Superset and Tableau

Superset and Tableau are both powerful data visualization tools, but they have some key differences. Here are six specific differences between the two:

User Interface: Superset offers a web-based user interface that is highly customizable and allows for interactive exploration of data. Tableau, on the other hand, provides a more user-friendly drag-and-drop interface that is suitable for users with less technical expertise.
Data Sources: While Tableau supports a wide range of data sources, including databases, spreadsheets, and cloud services, Superset has native support for SQL databases only. This means that Superset may be more suitable for organizations that primarily work with SQL databases.
Integration: Tableau offers seamless integration with various data management and analytics platforms, such as Salesforce and Hadoop, allowing users to easily import and analyze data from these sources. Superset, on the other hand, lacks such extensive integration capabilities, making it less suitable for organizations with diverse data sources.
Pricing Model: Tableau follows a subscription-based pricing model, which can be costly for organizations that require multiple licenses. In contrast, Superset is an open-source tool, meaning that it is free to use and can be customized as per the organization's needs.
Community Support: Tableau has a large and active user community, with extensive documentation, forums, and knowledge-sharing platforms, making it easier for users to find support and solutions to their problems. Superset, being a relatively newer tool, has a smaller community, which may limit the availability of resources for users seeking assistance.
Advanced Analytics: Tableau offers a wide range of advanced analytics features, including predictive modeling, statistical analysis, and data blending, enabling users to gain deeper insights from their data. Superset, on the other hand, focuses mainly on data visualization and lacks some of the advanced analytics capabilities offered by Tableau.

Superset vs Tableau

Overview

Superset vs Tableau: What are the differences?