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  5. Apache Zeppelin vs Superset

Apache Zeppelin vs Superset

OverviewComparisonAlternatives

Overview

Apache Zeppelin
Apache Zeppelin
Stacks190
Followers306
Votes32
GitHub Stars6.6K
Forks2.8K
Superset
Superset
Stacks420
Followers1.0K
Votes45

Apache Zeppelin vs Superset: What are the differences?

Introduction

Apache Zeppelin and Superset are both powerful data visualization tools that can be used in website development. While they share some similarities in terms of functionality, there are key differences that set them apart. This article aims to highlight the main differences between Apache Zeppelin and Superset.

  1. Interactivity: One key difference between Apache Zeppelin and Superset is their level of interactivity. Apache Zeppelin provides a highly interactive environment for data exploration, analysis, and visualization. Users can interact with the data, execute queries, and create visualizations in real-time. On the other hand, Superset offers a more static experience with pre-defined dashboards and charts. While Superset allows some level of interaction, it is not as dynamic as Apache Zeppelin.

  2. Supported Databases: Another important difference between Apache Zeppelin and Superset lies in their supported databases. Apache Zeppelin offers support for a wide range of databases, including popular ones like Apache Spark, MySQL, PostgreSQL, and others. This flexibility allows users to connect to various data sources and perform their analysis seamlessly. In contrast, Superset has a limited number of supported databases, which can be a consideration for organizations with diverse data sources.

  3. Built-in Notebooks: Apache Zeppelin is primarily known for its notebook interface, which allows users to create and share interactive documents. These notebooks can contain code, visualizations, and text, making it easy to document and reproduce analysis workflows. Superset, on the other hand, does not have a built-in notebook feature. While it offers a user-friendly interface for creating visualizations and dashboards, it lacks the notebook's functionality provided by Zeppelin.

  4. Collaboration and Sharing: Collaboration and sharing capabilities differ between Apache Zeppelin and Superset. Apache Zeppelin excels in this aspect, allowing users to share and collaborate on notebooks with other team members. Zeppelin also supports version control, making it easy to track changes and revert to previous versions if needed. In contrast, Superset focuses more on sharing dashboards and visualizations, without providing extensive collaboration features like Zeppelin.

  5. Data Source Integration: When it comes to integrating data from external sources, Apache Zeppelin offers more flexibility compared to Superset. Zeppelin allows users to ingest data from various sources using built-in connectors and libraries. This makes it easier to work with diverse datasets and leverage external libraries for analysis. Superset, while supporting various data sources, may require more manual configuration and customization to integrate data from specific sources.

  6. Customization and Extensibility: Lastly, Apache Zeppelin offers more customization and extensibility options compared to Superset. Zeppelin allows users to define custom visualizations, extend functionality with plugins, and customize the entire user interface to fit specific requirements. Superset, although customizable to some extent, may not provide the same level of flexibility when it comes to advanced customization and extending core functionality.

In summary, the key differences between Apache Zeppelin and Superset lie in their interactivity, supported databases, built-in notebook feature, collaboration capabilities, data source integration, and customization/extensibility options. These differences affect the user experience, data analysis capabilities, and flexibility of the tools in different ways.

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Detailed Comparison

Apache Zeppelin
Apache Zeppelin
Superset
Superset

A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.

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.

-
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
GitHub Stars
6.6K
GitHub Stars
-
GitHub Forks
2.8K
GitHub Forks
-
Stacks
190
Stacks
420
Followers
306
Followers
1.0K
Votes
32
Votes
45
Pros & Cons
Pros
  • 7
    In-line code execution using paragraphs
  • 5
    Cluster integration
  • 4
    Zeppelin context to exchange data between languages
  • 4
    In-line graphing
  • 4
    Multi-User Capability
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
Cassandra
Cassandra
Apache Spark
Apache Spark
R Language
R Language
PostgreSQL
PostgreSQL
Elasticsearch
Elasticsearch
HBase
HBase
Hadoop
Hadoop
Apache Flink
Apache Flink
Python
Python
No integrations available

What are some alternatives to Apache Zeppelin, 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.

Jupyter

Jupyter

The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.

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.

Mode

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

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.

Deepnote

Deepnote

Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore and analyze it with real-time collaboration and versioning, and easily share and present the polished assets to end users.

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.

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