Posit vs. Pytorch

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Posit
Score 9.1 out of 10
N/A
Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.N/A
Pytorch
Score 9.4 out of 10
N/A
Pytorch is an open source machine learning (ML) framework boasting a rich ecosystem of tools and libraries that extend PyTorch and support development in computer vision, NLP and or that supports other ML goals.N/A
Pricing
PositPytorch
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
PositPytorch
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details
More Pricing Information
Community Pulse
PositPytorch
Top Pros

No answers on this topic

Top Cons

No answers on this topic

Features
PositPytorch
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Posit
7.2
26 Ratings
16% below category average
Pytorch
-
Ratings
Connect to Multiple Data Sources8.025 Ratings00 Ratings
Extend Existing Data Sources7.326 Ratings00 Ratings
Automatic Data Format Detection6.325 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Posit
8.5
26 Ratings
1% above category average
Pytorch
-
Ratings
Visualization8.526 Ratings00 Ratings
Interactive Data Analysis8.523 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Posit
8.3
25 Ratings
1% above category average
Pytorch
-
Ratings
Interactive Data Cleaning and Enrichment8.223 Ratings00 Ratings
Data Transformations8.325 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Posit
8.2
21 Ratings
4% below category average
Pytorch
-
Ratings
Multiple Model Development Languages and Tools8.221 Ratings00 Ratings
Single platform for multiple model development8.421 Ratings00 Ratings
Self-Service Model Delivery8.018 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Posit
8.8
17 Ratings
3% above category average
Pytorch
-
Ratings
Flexible Model Publishing Options8.517 Ratings00 Ratings
Security, Governance, and Cost Controls9.115 Ratings00 Ratings
Best Alternatives
PositPytorch
Small Businesses
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.2 out of 10
Posit
Posit
Score 9.1 out of 10
Enterprises
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
IBM SPSS Modeler
IBM SPSS Modeler
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
PositPytorch
Likelihood to Recommend
9.1
(122 ratings)
9.4
(5 ratings)
Likelihood to Renew
9.7
(17 ratings)
-
(0 ratings)
Usability
10.0
(3 ratings)
-
(0 ratings)
Availability
9.4
(3 ratings)
-
(0 ratings)
Support Rating
8.9
(9 ratings)
-
(0 ratings)
Implementation Rating
9.3
(4 ratings)
-
(0 ratings)
Configurability
10.0
(1 ratings)
-
(0 ratings)
Product Scalability
8.2
(3 ratings)
-
(0 ratings)
User Testimonials
PositPytorch
Likelihood to Recommend
Posit (formerly RStudio)
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.
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Open Source
They have created Pytorch Lightening on top of Pytorch to make the life of Data Scientists easy so that they can use complex models they need with just a few lines of code, so it's becoming popular. As compared to TensorFlow(Keras), where we can create custom neural networks by just adding layers, it's slightly complicated in Pytorch.
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Pros
Posit (formerly RStudio)
  • 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.
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Open Source
  • Provides Benchmark datasets to test your custom algorithm
  • Provides with a lot of pre-coded neural net components to use for your flow
  • Gives a framework to write really abstract code.
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Cons
Posit (formerly RStudio)
  • 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.
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Open Source
  • Distributed data parallel still seems to be complicated
  • Support for easy deployment to servers
  • Torchvision to have support for latest models with pertained weights
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Likelihood to Renew
Posit (formerly RStudio)
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.
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Open Source
No answers on this topic
Usability
Posit (formerly RStudio)
I think it's a quick and easy to use tool. The IDE is very intuitive and easy to adapt to. You do not need to learn a lot of things to use this tool. Any programmer and a person with knowledge or R can quick use this tool without issues.
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Open Source
No answers on this topic
Reliability and Availability
Posit (formerly RStudio)
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
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Open Source
No answers on this topic
Support Rating
Posit (formerly RStudio)
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.
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Open Source
No answers on this topic
Implementation Rating
Posit (formerly RStudio)
We did it at the individual level: anyone willing to code in R can use it. No real deployment involved.
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Open Source
No answers on this topic
Alternatives Considered
Posit (formerly RStudio)
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.
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Open Source
As I described in previous statements, Pytorch is much better suited than TensorFlow from a software development look. This Pythonic idea was then taken and repeated by all the other frameworks. You can get to better performance models by better understanding the deep learning model code, so I think the choice of Pytorch is easy and simple.
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Scalability
Posit (formerly RStudio)
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.
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Open Source
No answers on this topic
Return on Investment
Posit (formerly RStudio)
  • 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).
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Open Source
  • I'd estimate I can build a model 50% faster on pytorch vs other frameworks
Read full review
ScreenShots

Posit Screenshots

Screenshot of Posit runs on most desktops or on a server and accessed over the webScreenshot of Posit supports authoring HTML, PDF, Word Documents, and slide showsScreenshot of Posit supports interactive graphics with Shiny and ggvisScreenshot of Shiny combines the computational power of R with the interactivity of the modern webScreenshot of Remote Interactive Sessions: Start R and Python processes from Posit Workbench within various systems such as Kubernetes and SLURM with Launcher.Screenshot of Jupyter: Author and edit Python code with Jupyter using the same Posit Workbench infrastructure.