Atmolytics Cloud vs Denodo
Overview
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Detailed Comparison
It is the leader in data virtualization providing data access, data governance and data delivery capabilities across the broadest range of enterprise, cloud, big data, and unstructured data sources without moving the data from their original repositories. | It is a data analysis and visualisation tool. Users can make sense of their data no matter what their skill level. The platform is simple and intuitive, and will even help you find the connection across complex data sets. |
Data virtualization;
Data query;
Data views | Empowering everyone with analytics capabilities;
Speed up your data exploration - Analyse and visualise large, multiple data sources in just a few clicks with powerful data discovery features;
Easily build custom dashboards and reports - Create rich, interactive dashboards, reports and visuals without needing database query or coding skills;
Share and collaborate with confidence - Maintain accuracy, consistency, and security while you collaborate on the same data |
Statistics | |
GitHub Stars 0 | GitHub Stars - |
GitHub Forks 0 | GitHub Forks - |
Stacks 40 | Stacks 0 |
Followers 120 | Followers 1 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |
What are some alternatives to Denodo, Atmolytics Cloud?
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.
Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more.
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.
NumPy
Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
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.
