AskNed vs Denodo

Overview

Denodo

Stacks40

Followers120

Votes0

GitHub Stars0

Forks0

AskNed

Stacks7

Followers14

Votes14

AskNed vs Denodo: What are the differences?

AskNed: Get answers from your data by just typing questions. AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English; Denodo: Data virtualisation platform, allowing you to connect disparate data from any source. 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.

AskNed and Denodo can be primarily classified as "Business Intelligence" tools.

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Detailed Comparison

Denodo	AskNed
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.	AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.
Data virtualization; Data query; Data views	Analytics Platform, NLP Technology, Enterprise Data Analytics
Statistics
GitHub Stars 0	GitHub Stars -
GitHub Forks 0	GitHub Forks -
Stacks 40	Stacks 7
Followers 120	Followers 14
Votes 0	Votes 14
Pros & Cons
No community feedback yet	Pros 3 Easy to use 3 Fast implementation 2 Good price 2 Awesome support 2 Super simple
Integrations
DataRobot AtScale Vertica Trifacta Dremio Apache Kylin SAP HANA	No integrations available

What are some alternatives to Denodo, AskNed?

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.

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.