GitHub is a platform that hosts public and private code and provides software development and collaboration tools. Features include version control, issue tracking, code review, team management, syntax highlighting, etc. Personal plans ($0-50), Organizational plans ($0-200), and Enterprise plans are available.
$4
per month per user
Posit
Score10 out of 10
N/A
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
N/A
Pricing
GitHub
Posit
Editions & Modules
Team
$40
per year per user
Enterprise
$210
per year per user
No answers on this topic
Offerings
Pricing Offerings
GitHub
Posit
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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More Pricing Information
Community Pulse
GitHub
Posit
Considered Both Products
GitHub
No answer on this topic
Posit (formerly RStudio)
Verified User
Chose Posit
RStudio stacks up pretty well against its competition. For me, it is really up to personal preference and what you are used to when deciding between the competitions. I like that Python packages have the most external resources, so it's easier to troubleshoot. But RStudio does …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Verified User
Chose Posit
These all work synergistically and fulfill slightly different roles. In general this is determined by complexity of task and the degree of training and expertise of the end user. RStudio works well for organisations looking to move into doing more complex analytics. In general …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
Graduate Research assistant in Research & Development at University of Vermont (Higher Education, 5001-10,000 employees)
Chose Posit
I like the simplicity of Rstudio, and besides the obvious point that PyCharm is an IDE for python, I find Rstudio much more intuitive. Plotting is better, Rstudio is much easier to customize, and PyCharm tends to take a long time to load. However, I have not experienced as much …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
GitHub is an easy to go tool when it comes to Version Controlling, CI/CD workflows, Integration with third party softwares. It's effective for any level of CI/CD implementation you would like to. Also the the cost of product is also very competitive and affordable. As of now GitHub lacks capabilities when it comes to detailed project management in comparison to tools like Jira, but overall its value for money.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
In my humble opinion, if you are working on something related to Statistics, RStudio is your go-to tool. But if you are looking for something in Machine Learning, look out for Python. The beauty is that there are packages now by which you can write Python/SQL in R. Cross-platform functionality like such makes RStudio way ahead of its competition. A couple of chinks in RStudio armor are very small and can be considered as nagging just for the sake of argument. Other than completely based on programming language, I couldn't find significant drawbacks to using RStudio. It is one of the best free software available in the market at present.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
Version control: GitHub provides a powerful and flexible Git-based version control system that allows teams to track changes to their code over time, collaborate on code with others, and maintain a history of their work.
Code review: GitHub's pull request system enables teams to review code changes, discuss suggestions and merge changes in a central location. This makes it easier to catch bugs and ensure that code quality remains high.
Collaboration: GitHub provides a variety of collaboration tools to help teams work together effectively, including issue tracking, project management, and wikis.
The support is incredibly professional and helpful, and they often go out of their way to help me when something doesn't work.
The one-click publishing from RStudio Connect is absolutely amazing, and I really like the way that it deploys your exact package versions, because otherwise, you can get in a terrible mess.
Python doesn't feel quite as native as R at the moment but I have definitely deployed stuff in R and Python that works beautifully which is really nice indeed.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Not an easy tool for beginners. Prior command-line experience is expected to get started with GitHub efficiently.
Unlike other source control platforms GitHub is a little confusing. With no proper GUI tool its hard to understand the source code version/history.
Working with larger files can be tricky. For file sizes above 100MB, GitHub expects the developer to use different commands (lfs).
While using the web version of GitHub, it has some restrictions on the number of files that can be uploaded at once. Recommended action is to use the command-line utility to add and push files into the repository.
Python integration is newer and still can be rough, especially with when using virtual environments.
RStudio Connect pricing feels very department focused, not quite an enterprise perspective.
Some of the RStudio packages don't follow conventional development guidelines (API breaking changes with minor version numbers) which can make supporting larger projects over longer timeframes difficult.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
GitHub's ease of use and continued investment into the Developer Experience have made it the de facto tool for our engineers to manage software changes. With new features that continue to come out, we have been able to consolidate several other SaaS solutions and reduce the number of tools required for each engineer to perform their job responsibilities.
There is no viable alternative right now. The toolset is good and the functionality is increasing with every release. It is backed by regular releases and ongoing development by the RStudio team. There is good engagement with RStudio directly when support is required. Also there's a strong and growing community of developers who provide additional support and sample code.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
GitHub is a clean and modern interface. The underlying integrations make it smooth to couple tasks, projects, pull requests and other business functions together. The insights and reporting is really strong and is getting better with every release. GitHub's PR tooling is strong for being web based, i do believe a better code editor would rival having to pull merge conflicts into local IDE.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
For someone who learns how to use the software and picks up on the "language" of R, it's very easy to use. For beginners, it can be hard and might require a course, as well as the appropriate statistical training to understand what packages to use and when
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
RStudio is very available and cheap to use. It needs to be updated every once in a while, but the updates tend to be quick and they do not hinder my ability to make progress. I have not experienced any RStudio outages, and I have used the application quite a bit for a variety of statistical analyses
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
There are a ton of resources and tutorials for GitHub online. The sheer number of people who use GitHub ensures that someone has the exact answer you are looking for. The docs on GitHub itself are very thorough as well. You will often find an official doc along with the hundreds of independent tutorials that answers your question, which is unusual for most online services.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Since R is trendy among statisticians, you can find lots of help from the data science/ stats communities. If you need help with anything related to RStudio or R, google it or search on StackOverflow, you might easily find the solution that you are looking for.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
While I don't have very much experience with these 2 solutions, they're two of the most popular alternatives to GitHub. Bitbucket is from Atlassian, which may make sense for a team that is already using other Atlassian tools like Jira, Confluence, and Trello, as their integration will likely be much tighter. Gitlab on the other hand has a reputation as a very capable GitHub replacement with some features that are not available on GitHub like firewall tools.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
RStudio was provided as the most customizable. It was also strictly the most feature-rich as far as enabling our organization to script, run, and make use of R open-source packages in our data analysis workstreams. It also provided some support for python, which was useful when we had R heavy code with some python threaded in. Overall we picked Rstudio for the features it provided for our data analysis needs and the ability to interface with our existing resources.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
RStudio is very scalable as a product. The issue I have is that it doesn't necessarily fit in nicely with the mainly Microsoft environment that everybody else is using. Having RStudio for us means dedicated servers and recruiting staff who know how to manage the environment. This isn't a fault of the product at all, it's just part of the data science landscape that we all have to put up with. Having said that RStudio is absolutely great for running on low spec servers and there are loads of options to handle concurrency, memory use, etc.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Team collaboration significantly improved as everything is clearly logged and maintained.
Maintaining a good overview of items will be delivered wrt the roadmap for example.
Knowledge management and tracking. Over time a lot of tickets, issues and comments are logged. GitHub is a great asset to go back and review why x was y.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Using it for data science in a very big and old company, the most positive impact, from my point of view, has been the ability of spreading data culture across the group. Shortening the path from data to value.
Still it's hard to quantify economic benefits, we are struggling and it's a great point of attention, since splitting out the contribution of the single aspects of a project (and getting the RStudio pie) is complicated.
What is sure is that, in the long run, RStudio is boosting productivity and making the process in which is embedded more efficient (cost reduction).
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
