Well, I like,yeah seriously like Codenvy for my JavaScript, PHP,Python projects and its cool, uncluttered UI fascinates me, keeps my head cool-the most important thing for a developer.

The  ease of use is pretty good , but its java editor is not the best especially compared eclipse. OTher wise codenvy is one of my favorites.

It worked on eclipse, and when I copy pasted the code, there was a compile error. I double checked with others, and they got similar errors.

Customer support is great. I like that the free version has an hour meter, but isn't limiting in any other way.

After trying Codenvy I am thoroughly impressed - this shouldn't be possible. I love the way they are taking advantage of containerization, and the UI is very well done.

Debugging Python limited compared to desktop IDE. Some of the pre-generated images lack a bit in description/documentation of what's where.

But what made me choose codenvy was is the great system they have built. It's fast, reliable and, so far, is working very nice to me.

Awesome tool for coding practice and some light app deployment.

It is just an amazing environment to code, debug and improve the effectiveness.

It is very good platform. It made very easy for coding ,testing and  deployment and deployment is free of cost.

I found and liked that Github was integrated making it easy to clone repos and push files over. Its pretty cool that there's keybinding for vi and emacs.

I started using this after I bought a low budget Chromebook. It really is an awesome cloud IDE and it supports than enough for a student like me.

The pricing is very much fair and you can share the workspaces with team members as well as external clients and members.

It can sometimes lag, or sometimes give me an error here or there, but at least it works.

I started using this to type C++ programs on the go, and it's a super user friendly. This is probably one of the best IDEs I've worked with.

Integration part gets very easy and is accessible from anywhere is a big advantage. No need to carry your laptop, makes more comfortable.

Some flaws of codenvy are its lag, and its occasional delays.

Amazing cloud development with great integrated tools even works with chrome books love it.

One thing that I dislike is that you have to pay for a subscription to have access to premium support.

It helps large groups and teams, the platform is easy to use.

I would definitely recommend Codenvy for a super easy, nice looking and reliable online IDE.

The most amazing with this is how easy you can share all that complex environment with a single click using the Factories.

These delays may not even be attributed to Codenvy itself, but may be a result of network connectivity problems or individual computer problems.

They have provided an ample number of tutorials to use codes, both automatic and source and the best part I love about this application is its customer service.

The best is that you don't need to download a heavy software and the progress is saved on the cloud.

After some adjusting, I have learned to love it. The ability to use it cross platform, on-the-fly via the Chrome Browser has become a Godsend.

Very affordable tool, quick and responsive customer service. Offers a cloud based coding system, is open source.

Powerful and robust open source coding system.

Same for their documentations it's amazing I love the categories really helpful and easy to do what you have to do.

Also It's very annoying that virtual machine powers off after several minutes. If I'm writing an application I need to relaunch my code quite often and these poweroffs are really frustrating.

R is one of the simplest programming languages and R-studio makes full use of its capabilities. The R community is amazing and provides immense support where needed.

Overall, I could write my desired code and do my job using powerful packages which were available.

Since it is open source there are many add ons that you can implement to the library to improve its functionality.

The problem of backwards compatibility of different versions of R and R packages is not an RStudio problem, and RStudio works with all versions of R and R packages.

It is super easy to use and convenient. Cheap compared to competitors.

Quite satisfied and content for R programming with RStudio.

The inability to create a collaboration project.

Ease of use, debugging, and GUI are the best in the buisiness when it comes to R IDEs.

RStudio is a delightful IDE for working with Rlang and data.

I can analyze and get beautiful and explanatory graphics in a few minutes. The coding part is very handy and it can be editing and saved so you do not lose any code or project for the future.

The user interface makes it extremely easy to organize and visualize data sets and it extremely useful for teaching. R studio is also easy to download and install and is free for individual users.

There are no major dislikes about R studio, being a free software it does depend on the open source community for continuing development, which can be arguably not beneficial to the software.

R studio is an improved version to manage and execute code in the R platform.

Highly recommended to the researchers who are handling large data set.

If you are looking for a free tool to do data analytics with RStudio will do what you need it to do. If ever given the option I will always use RapidMiner or another software that has a better GUI.

Overall, I love how powerful it is and like how many different packages are available.

Great open source software for data and statistical analysis, user friendly and minimized code writing, good supportive libraries and great infographs.

I have found using RStudio intuitive, easy, and fun to use.

The layout of the screen and the ability to break out separate windows is really great and makes using the software on a single screen or multiple screens very friendly.

As every programming language it may a bit difficult at the start to learn.

In my opinion, Rstudio provides the best environment to be used by statisticians and data scientists. The software is great and its supporting website provides a lot of tutorials.

I typically use RStudio to solve research issues such as data analysis of growth mindset. I would highly recommend it for free, convenient data analyses.

The very best second thing is this is open-source software( you do not need to buy it).

The ability to install missing R packages instantly, creating R Markdown documents, and integration with Shiny Web App are the most appealing features for me as a machine learning researcher.

A GUI interface for data manipulation and visualisation.

I also found it difficult to intergrate R studio with other languages such as python or C. It also seems catered to more of a data science analysis approach rather than programming and execution.

R-studio automatically updates periodically which can be a pain. Also, it cannot run multiple queries at the same time.

R Studio - larger learning curve than SPSS but will save you money.

Overall R studio is an excellent product and a great tool to supplement teaching statistics and algebra II at the high school level and any statistics and data science class at the college algebra.

It's a great software which generate outputs very easily using a coding system. And also it includes thousands of useful packages.

Also plotting graphs, curve fittings etc can be done with ease.

I really love how versatile it is in creating professional looking graphics and tables, as well as how intuitive the syntax is to learn.

Awesome light and dark mode for user preferences. Direct git integrations for faster and convenient coding with collaboration.

My overall experience with R-Studio has been positive and I have been able to effectively analyze a large amount of data and write papers on it.

Amazing matematical programming language. I use it often in my job to perform data analysis.

Rstudio can be very confusing at times, and as a code editor, sometimes the errors do not make sense.

Objects' explorer is a must in data science, and Rstudio's is particularly good for exploring and giving lot of information about every object in a glimpse. Multi-platform: GNU/Linux, Windows, Mac.

R Studio is my sought after Machine learning programme, I am so fascinated about how to use it scale business. All our credit models are built in R.

R is an amazing programming language designed to perform statistical analysis and calculations.

It is the swiss army tool of a data-scientist. Thanks to its huge community any doubt you may have can be replied easily by a simple search on internet, or by asking in forums.

It's clean, sleek interface is very intuitive and user friendly. It can handle large amounts of data and it suggests functions as you type, making it very beginner friendly.

Although GGPLOT package provides a lot of features for graphical representations, it is very difficult to handle.

The major disadvantage is the inability to use it for core code development, lack of flexibility in writing deep learning or neural network  models.

I love the price of R/Rstudio - free. Competitors such as SPSS/IBM are expensive for one year licenses.

US Dollar

Codenvy is a workspace platform for development and operations professionals. It enables users to edit, run and debug code. It offers cloud-based and on-premise deployments.


When users begin a new project, production runtimes are defined by existing Docker and Compose files. Runtimes are configured so developers can connect to them, and workspace agents inject root-privileged terminal, language services for auto-completion, and SSH access. Finally, a debugger is connected for code inspection.


Codenvy virtual workspaces allow developers to edit, save, build and debug code as though it were local. Workspaces can use the Eclipse Che browser-integrated development environment (IDE) or sync a desktop IDE. Workspaces can be shared within teams or with external users, and administrators can set user permissions and resources for each user. Integrations include JIRA and Jenkins.


Condenvy is available with subscription pricing. Support is available via email and through Github.



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RStudio is an integrated development environment for R and Python. This software is ideal for data scientists, DevOps engineers, and IT admins. It includes a console, syntax-highlighting editor that supports direct code execution, as well as tools for plotting, history, debugging, and workspace management.

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