PyGWalker vs Sigma Computing
Overview
🔥 Trending in Business Intelligence on StackShare
Detailed Comparison
It is modern analytics built for the cloud. Trusted by data-first companies, it provides live access to cloud data warehouses using an intuitive spreadsheet interface that empowers business experts to ask more questions without writing a single line of code. With the full power of SQL, the cloud, and a familiar interface, business users have the freedom to analyze data in real time without limits. | It is a Python library for Exploratory Data Analysis with visualization. It can simplify your Jupyter Notebook data analysis and data visualization workflow, by turning your pandas dataframe into a Tableau-style User Interface for visual exploration. |
Ad Hoc Reports; Benchmarking; Dashboard; Key Performance Indicators ;Performance Metrics; Predictive Analytics; Visual Analytics; Embedded Dashboards; SQL runner; Self-service Analytics; Visual Data Modeling | Exploratory Data Analysis with visualization;
Simplify your Jupyter Notebook data analysis |
Statistics | |
GitHub Stars - | GitHub Stars 15.4K |
GitHub Forks - | GitHub Forks 842 |
Stacks 21 | Stacks 2 |
Followers 27 | Followers 3 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Sigma Computing, PyGWalker?
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.
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.
