Knowage vs Superset

Overview

Superset

Stacks420

Followers1.0K

Votes45

Knowage

Stacks4

Followers15

Votes0

GitHub Stars430

Forks231

Knowage vs Superset: What are the differences?

Introduction

Knowage and Superset are two popular open-source data visualization and analytics platforms. While they share some similarities, there are key differences that set them apart from each other. Below are the six main differences between Knowage and Superset.

User Interface and Ease of Use: Knowage provides a more traditional and structured user interface with various menus and toolbars, making it suitable for users who prefer a more guided experience. On the other hand, Superset offers a more modern and customizable user interface with drag-and-drop capabilities, allowing users to create dashboards and visualizations with great flexibility and ease.
Data Source Connectivity: Knowage supports a wide range of data sources, including traditional databases, big data platforms, and NoSQL systems. It also provides functionalities to connect to RESTful APIs and web services. Meanwhile, Superset focuses primarily on database connectivity and provides extensive support for SQL-based data sources, such as MySQL, PostgreSQL, and Druid.
Advanced Analytics and Data Exploration: Knowage offers a comprehensive set of advanced analytics features, including predictive modeling, data mining, and what-if analysis. It also provides OLAP (Online Analytical Processing) capabilities for multidimensional analysis. While Superset has basic analytics functionalities, its primary strength lies in data exploration and visualization, allowing users to create interactive visualizations and explore data in real-time.
Security and Access Control: Knowage emphasizes security and offers robust access control mechanisms to ensure data confidentiality and integrity. It provides fine-grained user permissions and role-based access control. In contrast, Superset provides basic user authentication and authorization features but lacks some of the advanced security capabilities offered by Knowage.
Community and Support: Knowage has a well-established and active community of users and developers, with regular updates and bug fixes. It also provides commercial support options for enterprise customers. Superset, although gaining popularity, has a relatively smaller community but benefits from being an Apache Software Foundation project, which ensures active development and community support.
Customization and Extensibility: Knowage allows users to customize the platform and extend its functionalities through plugins and extensions. It also provides a dedicated marketplace for sharing and downloading custom components. Superset, being an open-source project, allows extensive customization and offers a wide range of visualization options. It also supports the creation of custom visualizations through its API.

In Summary, Knowage offers a structured user interface, advanced analytics capabilities, and strong security features, while Superset provides a modern and customizable user interface, focuses on data exploration and visualization, and has a growing community of users and developers.

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CLI (Node.js)

Manual

Detailed Comparison

Superset	Knowage
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.	It is composed of several modules, each one conceived for a specific analytical domain. They can be used individually or combined with one another to ensure full coverage of user’ requirements, allowing to build a tailored product.
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;	Big Data; Smart Intelligence; Enterprise Reporting; Location Intelligence; Performance Management; Predictive Analysis; Embedded Intelligence
Statistics
GitHub Stars -	GitHub Stars 430
GitHub Forks -	GitHub Forks 231
Stacks 420	Stacks 4
Followers 1.0K	Followers 15
Votes 45	Votes 0
Pros & Cons
Pros 13 Awesome interactive filtering 9 Free 6 Wide SQL database support 6 Shareable & editable dashboards 5 Great for data collaborating on data exploration Cons 4 Link diff db together "Data Modeling " 3 It is difficult to install on the server 3 Ugly GUI	No community feedback yet
Integrations
No integrations available	Apache Spark

What are some alternatives to Superset, Knowage?

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

Knowage vs Superset: What are the differences?

Introduction

User Interface and Ease of Use: Knowage provides a more traditional and structured user interface with various menus and toolbars, making it suitable for users who prefer a more guided experience. On the other hand, Superset offers a more modern and customizable user interface with drag-and-drop capabilities, allowing users to create dashboards and visualizations with great flexibility and ease.
Data Source Connectivity: Knowage supports a wide range of data sources, including traditional databases, big data platforms, and NoSQL systems. It also provides functionalities to connect to RESTful APIs and web services. Meanwhile, Superset focuses primarily on database connectivity and provides extensive support for SQL-based data sources, such as MySQL, PostgreSQL, and Druid.
Advanced Analytics and Data Exploration: Knowage offers a comprehensive set of advanced analytics features, including predictive modeling, data mining, and what-if analysis. It also provides OLAP (Online Analytical Processing) capabilities for multidimensional analysis. While Superset has basic analytics functionalities, its primary strength lies in data exploration and visualization, allowing users to create interactive visualizations and explore data in real-time.
Security and Access Control: Knowage emphasizes security and offers robust access control mechanisms to ensure data confidentiality and integrity. It provides fine-grained user permissions and role-based access control. In contrast, Superset provides basic user authentication and authorization features but lacks some of the advanced security capabilities offered by Knowage.
Community and Support: Knowage has a well-established and active community of users and developers, with regular updates and bug fixes. It also provides commercial support options for enterprise customers. Superset, although gaining popularity, has a relatively smaller community but benefits from being an Apache Software Foundation project, which ensures active development and community support.
Customization and Extensibility: Knowage allows users to customize the platform and extend its functionalities through plugins and extensions. It also provides a dedicated marketplace for sharing and downloading custom components. Superset, being an open-source project, allows extensive customization and offers a wide range of visualization options. It also supports the creation of custom visualizations through its API.

Knowage vs Superset

Overview