Denodo vs Mineo
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 the platform to explore your data, develop and deploy your Python supercharged Notebooks and track the quality of your data using Machine learning. |
Data virtualization;
Data query;
Data views | Develop, share and deploy your supercharged Python notebooks on a scalable platform;
Automate and streamline your workflows with Python-based data pipelines that leverage the power of notebooks;
Establish processes to measure and track the quality of your data over the time using machine learning |
Statistics | |
GitHub Stars 0 | GitHub Stars - |
GitHub Forks 0 | GitHub Forks - |
Stacks 40 | Stacks 0 |
Followers 120 | Followers 1 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Denodo, Mineo?
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.
Jupyter
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
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.
Apache Zeppelin
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
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.
