Flask JSONDash vs Google Datastudio

Overview

Flask JSONDash

Stacks16

Followers48

Votes3

GitHub Stars3.3K

Forks300

Google Datastudio

Stacks200

Followers170

Votes16

Flask JSONDash vs Google Datastudio: What are the differences?

Flask JSONDash: A flask app to make dashboards, easily. Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only. Ready to go; Google Datastudio: A reporting and data visualization tool. 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.

Flask JSONDash and Google Datastudio belong to "Business Intelligence" category of the tech stack.

Flask JSONDash is an open source tool with 2.91K GitHub stars and 252 GitHub forks. Here's a link to Flask JSONDash's open source repository on GitHub.

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Detailed Comparison

Flask JSONDash	Google Datastudio
Easily configurable, chart dashboards from any arbitrary API endpoint. JSON config only. Ready to go.	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.
-	Easily access a wide variety of data. Data Studio’s built-in and partner connectors makes it possible to connect to virtually any kind of data Turn your data into compelling stories of data visualization art. Quickly build interactive reports and dashboards with Data Studio’s web based reporting tools Share your reports and dashboards with individuals, teams, or the world. Collaborate in real time. Embed your report on any web page
Statistics
GitHub Stars 3.3K	GitHub Stars -
GitHub Forks 300	GitHub Forks -
Stacks 16	Stacks 200
Followers 48	Followers 170
Votes 3	Votes 16
Pros & Cons
Pros 2 Very flexible for ad-hoc sources 1 Simple 0 Righteous Dudes	Pros 6 Free 4 Underrated 2 Easy to share 1 Google Analytics Integration 1 BigQuery Integration Cons 1 Works well with google (not aws or azure)
Integrations
No integrations available	MySQL Microsoft SQL Server Microsoft Excel

What are some alternatives to Flask JSONDash, Google Datastudio?

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.

Superset

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.

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.

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.