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  5. Denodo vs Orchest

Denodo vs Orchest

OverviewComparisonAlternatives

Overview

Denodo
Denodo
Stacks40
Followers120
Votes0
GitHub Stars0
Forks0
Orchest
Orchest
Stacks1
Followers12
Votes0
GitHub Stars4.1K
Forks264

Orchest vs Denodo: What are the differences?

Orchest: An open source tool for creating data science pipelines. It is a web-based data science tool that works on top of your filesystem allowing you to use your editor of choice. With Orchest you get to focus on visually building and iterating on your pipeline ideas. Under the hood Orchest runs a collection of containers to provide a scalable platform that can run on your laptop as well as on a large scale cloud cluster; 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.

Orchest can be classified as a tool in the "Data Science Tools" category, while Denodo is grouped under "Business Intelligence".

Some of the features offered by Orchest are:

  • Visual pipeline editor
  • Executable notebooks
  • Open source

On the other hand, Denodo provides the following key features:

  • Data virtualization
  • Data query
  • Data views

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Detailed Comparison

Denodo
Denodo
Orchest
Orchest

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 web-based data science tool that works on top of your filesystem allowing you to use your editor of choice. With Orchest you get to focus on visually building and iterating on your pipeline ideas. Under the hood Orchest runs a collection of containers to provide a scalable platform that can run on your laptop as well as on a large scale cloud cluster.

Data virtualization; Data query; Data views
Visual pipeline editor; Executable notebooks; Open source
Statistics
GitHub Stars
0
GitHub Stars
4.1K
GitHub Forks
0
GitHub Forks
264
Stacks
40
Stacks
1
Followers
120
Followers
12
Votes
0
Votes
0
Integrations
DataRobot
DataRobot
AtScale
AtScale
Vertica
Vertica
Trifacta
Trifacta
Dremio
Dremio
Apache Kylin
Apache Kylin
SAP HANA
SAP HANA
Pandas
Pandas
dbt
dbt
Python
Python
R Language
R Language
Matplotlib
Matplotlib
TensorFlow
TensorFlow
Streamlit
Streamlit
PyTorch
PyTorch
Dask
Dask
Jupyter
Jupyter

What are some alternatives to Denodo, Orchest?

Metabase

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

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

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

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

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

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

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

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

AskNed is an analytics platform where enterprise users can get answers from their data by simply typing questions in plain English.

Shiny

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.

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