Azure DevOps (formerly VSTS, Microsoft Visual Studio Team System) is an agile development product that is an extension of the Microsoft Visual Studio architecture. Azure DevOps includes software development, collaboration, and reporting capabilities.
$2
per GB (first 2GB free)
Posit
Score 10.0 out of 10
N/A
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
N/A
Pricing
Azure DevOps
Posit
Editions & Modules
Azure Artifacts
$2
per GB (first 2GB free)
Basic Plan
$6
per user per month (first 5 users free)
Azure Pipelines - Self-Hosted
$15
per extra parallel job (1 free parallel job with unlimited minutes)
Azure Pipelines - Microsoft Hosted
$40
per parallel job (1,800 minutes free with 1 free parallel job)
Basic + Test Plan
$52
per user per month
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Offerings
Pricing Offerings
Azure DevOps
Posit
Free Trial
No
Yes
Free/Freemium Version
No
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
Azure DevOps
Posit
Considered Both Products
Azure DevOps
No answer on this topic
Posit
Verified User
Engineer
Chose Posit
For R programming, it's the de-facto because it's designed specifically for it, but other language support is getting stronger.
Azure DevOps works well when you’ve got larger delivery efforts with multiple teams and a lot of moving parts, and you need one place to plan work, track it properly, and see how everything links together. It’s especially useful when delivery and development are closely tied and you want backlog items, code and releases connected rather than spread across tools. Where it’s less of a fit is for small teams or simple pieces of work, as it can feel like more setup and process than you really need, and non-technical users often struggle with the interface. It also isn’t great if you want instant, easy programme-level views or a very visual planning experience without putting time into configuration.
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.
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.
I did mention it has good visibility in terms of linking, but sometimes items do get lost, so if there was a better way to manage that, that would be great.
The wiki is not the prettiest thing to look at, so it could have refinements there.
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.
I don't think our organization will stray from using VSTS/TFS as we are now looking to upgrade to the 2012 version. Since our business is software development and we want to meet the requirements of CMMI to deliver consistent and high quality software, this SDLC management tool is here to stay. In addition, our company uses a lot of Microsoft products, such as Office 365, Asp.net, etc, and since VSTS/TFS has proved itself invaluable to our own processes and is within the Microsoft family of products, we will continue to use VSTS/TFS for a long, long time.
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.
It's a great help to get more information about new feature release and stay updated on what the dev team is working on. I like how easy it is to just login and read through the work items. Each work item has basic details: Title, Description, Assigned to, State, Area (what it belongs to), and iteration (when it’s worked on). See image above.They move through different states (New → Discovery → Ready for Prod → etc.).
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
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
When we've had issues, both Microsoft support and the user community have been very responsive. DevOps has an active developer community and frankly, you can find most of your questions already asked and answered there. Microsoft also does a better job than most software vendors I've worked with creating detailed and frequently updated documentation.
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.
Microsoft Planner is used by project managers and IT service managers across our organization for task tracking and running their team meetings. Azure DevOps works better than Planner for software development teams but might possibly be too complex for non-software teams or more business-focused projects. We also use ServiceNow for IT service management and this tool provides better analysis and tracking of IT incidents, as Azure DevOps is more suited to development and project work for dev teams.
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.
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.
We have saved a ton of time not calculating metrics by hand.
We no longer spend time writing out cards during planning, it goes straight to the board.
We no longer track separate documents to track overall department goals. We were able to create customized icons at the department level that lets us track each team's progress against our dept goals.
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).
