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  5. Numeracy vs Superset

Numeracy vs Superset

OverviewComparisonAlternatives

Overview

Superset
Superset
Stacks420
Followers1.0K
Votes45
Numeracy
Numeracy
Stacks1
Followers10
Votes0

Numeracy vs Superset: What are the differences?

Developers describe Numeracy as "A SQL pad that gives you x-ray vision for your data". Numeracy is a lightweight SQL pad that gives you powerful querying and visualization for your data warehouse. On the other hand, Superset is detailed as "Data exploration and visualization platform, by Airbnb". 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.

Numeracy and Superset can be categorized as "Business Intelligence" tools.

Some of the features offered by Numeracy are:

  • Interactive tables
  • Smarter suggestions
  • Shareable links

On the other hand, Superset provides the following key features:

  • 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

Superset is an open source tool with 25.1K GitHub stars and 4.83K GitHub forks. Here's a link to Superset's open source repository on GitHub.

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CLI (Node.js)
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Manual

Detailed Comparison

Superset
Superset
Numeracy
Numeracy

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.

Numeracy is a lightweight SQL pad that gives you powerful querying and visualization for your data warehouse.

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;
Interactive tables; Smarter suggestions; Shareable links; Built for speed; Quick start; Query history; Push to Slack (beta)
Statistics
Stacks
420
Stacks
1
Followers
1.0K
Followers
10
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
Microsoft SQL Server
Microsoft SQL Server
Amazon Redshift
Amazon Redshift
Presto
Presto
MySQL
MySQL
PostgreSQL
PostgreSQL
Google BigQuery
Google BigQuery

What are some alternatives to Superset, Numeracy?

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.

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.

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.

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