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  5. Mode vs Superset

Mode vs Superset

OverviewDecisionsComparisonAlternatives

Overview

Mode
Mode
Stacks125
Followers227
Votes17
Superset
Superset
Stacks420
Followers1.0K
Votes45

Mode vs Superset: What are the differences?

Introduction

In this Markdown formatted content, we will discuss and compare the key differences between Mode and Superset, which are two popular data analysis and visualization tools. Both Mode and Superset serve similar purposes in helping users make sense of data, but they have distinct features and functionalities that set them apart.

  1. Mode: Mode is a comprehensive and user-friendly data analysis and visualization platform. It offers a wide range of features that enable users to perform complex data analysis tasks, including data exploration, SQL querying, and interactive visualizations. One key differentiating factor of Mode is its collaboration capabilities, allowing multiple users to work on the same project and share insights in real-time.

  2. Superset: Superset, on the other hand, is an open-source, web-based data exploration and visualization tool. It provides a rich set of visualization options and facilitates interactive exploration of large datasets. One notable advantage of Superset is its extensibility, whereby users can incorporate custom visualizations and integrate with external libraries to create more advanced dashboards and reports.

  3. Mode's SQL Editor: Mode offers a powerful SQL editor that allows users to write and execute SQL queries against their datasets. This built-in editor provides features such as auto-complete, syntax highlighting, and result previews, making it easier for users to manipulate and analyze their data efficiently. Superset, although it also supports SQL querying, does not have as comprehensive of an SQL editor as Mode.

  4. Superset's Charting Capabilities: Superset excels in its charting capabilities, offering a wide variety of visualizations and options for customization. It provides an intuitive interface for creating beautiful and interactive charts, allowing users to easily explore and present their data in meaningful ways. While Mode also has visualization features, Superset's focus on charting sets it apart as a dedicated visualization tool.

  5. Mode's Collaboration Features: As mentioned earlier, Mode emphasizes collaboration by allowing users to work together on data analysis projects. It offers shared workspaces, collaborative notebooks, and the ability to comment and share insights with other users. This collaborative aspect makes Mode a valuable tool for teams working on data-related tasks. Superset, although it provides user access control, does not have the same level of collaboration features as Mode.

  6. Superset's Community Contribution: Superset is an open-source tool with a thriving community of contributors. This means that there is a constant stream of updates, bug fixes, and new features being added to the platform. The community actively maintains and supports Superset, making it a reliable choice for users who value the open-source ecosystem. Mode, while it provides excellent support, does not have the same degree of community contribution and openness.

In summary, Mode and Superset are both powerful data analysis and visualization tools. However, Mode focuses more on collaboration and provides a robust SQL editor, while Superset offers extensive charting capabilities, customizability, and benefits from an active open-source community. Choosing between the two depends on specific requirements and preferences of users.

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Advice on Mode, Superset

icanautomate
icanautomate

Apr 13, 2021

Review

Hey Alfaz, the tools you mentioned are not exactly BI tools and are essentially ELT tools meant to collect data from third-party data sources (tools used for sales, marketing, advertising, etc) and ingest the data into a data warehouse (Snowflake, Redshift, BigQuery, etc). You can check out the linked article to learn more.

I have also recommended some BI tools like Mode, Looker, and SiSense. Happy to answer follow-up questions!

15 views15
Comments
Wei
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

Mode
Mode
Superset
Superset

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.

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.

Write, save, and share SQL queries with other analysts in your company; Empower non-technical folks to update queries on their own; Run queries on a schedule, create lists of related reports, and explore a project's history as it changes over time; Build reports using standard charting or create completely customer, interactive visuals with HTML, CSS, and Javascript;Database connectors for MySQL, Postgres, Redshift, Vertica, Hive, Heroku, Segment, BigQuery, Impala; Mode also offers SQL School (sqlschool.modeanalytics.com), a free, interactive SQL tutorial and the Mode Playbook.
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
125
Stacks
420
Followers
227
Followers
1.0K
Votes
17
Votes
45
Pros & Cons
Pros
  • 4
    Empowering for SQL-first analysts
  • 3
    Collaborative query building
  • 3
    Easy report building
  • 2
    Integrated IDE with SQL + Python for analysis
  • 2
    In-app customer chat support
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
Integrations
Apache Hive
Apache Hive
Microsoft Azure
Microsoft Azure
Google BigQuery
Google BigQuery
Apache Impala
Apache Impala
Amazon Redshift
Amazon Redshift
PostgreSQL
PostgreSQL
Segment
Segment
MySQL
MySQL
Microsoft SQL Server
Microsoft SQL Server
No integrations available

What are some alternatives to Mode, Superset?

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.

Cube

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

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.

Google Datastudio

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

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

Shiny

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

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

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

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

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.

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