Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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SAS Viya
Score 6.8 out of 10
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An end-to-end platform for AI, data science, and analytics, used for modeling, as well as management and deployment of AI models.
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Pricing
Posit
SAS Viya
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Posit
SAS Viya
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Posit
SAS Viya
Considered Both Products
Posit
Verified User
Anonymous
Chose Posit
SPSS is good for folks who are not as familiar with statistics, and for those who are older or more technologically-experienced and may be overwhelmed by Posit's products. It's also really great for teaching students and getting them exposed. However, because Posit is free, …
Posit is far better than Jupyter Notebook and Minitab in this regard that Posit is actually capable of doing all kind of analytical stuffs like data pre-processing, wrangling, validation and visualization. On the other hand, Jupyter Notebook can be used for python programming …
Posit is way way way more reliable than Excel for anything more involved than a quick spreadsheet. Faster speeds, greater charting abilities, flexible functionality and more efficient memory usage. Python is still my go-to for anything that needs integration, but Posit beats …
I've used ArcGIS and ESRI for similar analysis and while both have their advantages, RStudio is much better suited for running advanced statistics and processing large volumes of data. It can also produce quality maps, however, for visually attractive maps and graphs, ArcGIS is …
RStudio is better than python for visualizations but it is less common to use it in many organizations. Excel and PowerBI are better for visualization but, they can only be used for simple models. I would choose R Studio for statistical analysis, ML, or DL because the language …
RStudio works really well compared to competitors such as Jupyter Notebook where there is no environment to visualize variables. RStudio on the other hand is much easier to use and provides the right set of environments for users.
inter-departmental collaboration - my first choice would be TIBCO Spotfire natural language processing and knowledge graphs - my first choice would be Python information security & visualizations (including d3.js libraries) - my first choice is RStudio
RStudio is more than a home for a dashboard. It is a content management system for data science. It hosts models, APIs, runs scripts, AND hosts dashboards.
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 …
The most similar products to RStudio that I have used include IBM SPSS and Tableau Prep. In my experience, SPSS is more intuitive and has less of a learning curve; I used it extensively in my undergraduate career in Statistics and Cognitive Science research. While RStudio has …
RStudio stacks up pretty well against Anaconda. However, Anaconda might be the first choice for someone who likes Python for their analytics and machine learning needs. In the past, I have found it seamless to connect Jupyter Notebook (in Anaconda suite) to integrate with other …
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 …
Personally, I would prefer SPSS over RStudio and SAS, but the cost for licenses for SPSS deters me from continuing to go with IBM's statistics software. RStudio has the advantage in that it is low cost and there are a lot of available resources on YouTube available for users …
Using [RStudio] requires greater knowledge of statistics and code than SPSS, which has a more simple "point and click" interface. [RStudio] is similar to SAS in its user interface and [requires] the user to write their own queries. [RStudio]'s main advantage is an open-source …
I tried Stata because it's a standard tool for economists but it doesn't have the flexibility and breadth of R and RStudio. I didn't try other IDEs for R.
RStudio is free and so that is the main reason that I use it. I like that it is open source and so there are lots of support on the internet. I tried SAS JMP and Python in a text editor but RStudio was better than either of those options for cost and code flexibility …
RStudio is as good as any software available in the market and is better off than some as it is free. Since it is open source it is improving day by day. I would prefer RStudio over any other tool any day. I would recommend every data analyst to give RStudio a try.
I understand the Jupyter notebook is supposed to be good like RStudio, and I've been exposed to it a little bit. But my experience using it has been very little.
I prefer SPSS to RStudio, but RStudio is very cheap in comparison to the cost of SPSS. IBM's SPSS does a better job holding the hands of users, but it does come at a very expensive license cost. RStudio is a little bit more difficult to use but is cheap.
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 …
There are loads of people in the BI (Business Intelligence) space, of course... but I wouldn't touch any of them because none of them offer anything like the R and Python support that RStudio does. RStudio publishes open-source, they're a public benefit corporation, and they …
SAS was the incumbent tool, and what the team knew. We did look into using Revolution Analytics enterprise version of R, but the learning curve on that caused us to stick with SAS. In my current position, I've opted for WPS over SAS. I can still leverage my SAS experience, but …
SAS is just as good as these tools but is pricier. I like that it handles data visualization and modeling together in one platform that's a novel mechanism that is fairly rare. Also, it's forecasting capabilities are nicely integrated with the functionality overall which makes …
We had major use of SAS in forecasting where it doesn't require high level of coding knowledge and which has highly efficient models built in which can give good results on forecasts without lot of manual intervention. This tool was designed specifically for forecasting and …
SAS is faster then both SPSS and STATA. SAS also has better models and graphs when comparing the three softwares. However, STATA and SPSS are more user friendly. It is easy to use SPSS and STATA, because a lot of it is point-click. SAS requires some training to be able to use …
Director, Application Architecture and Programming
Chose SAS Viya
SAS has a much superior and comprehensive data preparation capability with a clear approach on how to handle and scale for a large amount of data and users. However, it can be more expensive to implement.
R is of course much cheaper (free) than SAS Analytics, and it can do everything SAS Analytics can do and more. It is a much more technical tool than SAS Analytics, which is why some people prefer SAS Analytics.
SAS allows the user a wider range of capabilities to cleanse and manipulate the data. Not only can the data be pulled directly into SAS, but before it is finalized it can be transposed, graphed, or altered in any way imaginable which puts it a step above the Business Objects …
Features
Posit
SAS Viya
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Posit
9.3
Ratings
11% above category average
SAS Viya
-
Ratings
Connect to Multiple Data Sources
8.00 Ratings
00 Ratings
Extend Existing Data Sources
10.00 Ratings
00 Ratings
Automatic Data Format Detection
10.00 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Posit
9.0
Ratings
7% above category average
SAS Viya
-
Ratings
Visualization
8.00 Ratings
00 Ratings
Interactive Data Analysis
10.00 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Posit
10.0
Ratings
20% above category average
SAS Viya
-
Ratings
Interactive Data Cleaning and Enrichment
10.00 Ratings
00 Ratings
Data Transformations
10.00 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Posit
10.0
Ratings
18% above category average
SAS Viya
-
Ratings
Multiple Model Development Languages and Tools
10.00 Ratings
00 Ratings
Single platform for multiple model development
10.00 Ratings
00 Ratings
Self-Service Model Delivery
10.00 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
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.
We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. It would be useful in analyzing population health metrics combined with financial data.
Ability to scale across the company is limited based on the users license, cannot share a dashboard to the general view of the company.
Ability to retain session - not simple method to customize view per user (e.g., once session is ended, the users will return next time to the baseline view).
Ability to enable communication between multiple users - leave notes, tag other users, or share specific view.
SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.
There is no other platform that meets our needs. Even if it was terrible we would still use it but fortunately for us it is a very solid project with a great support team. I hope in the future to expand our use and get more licences as well as upgrade to RStudio workbench but for now we are very happy.
Not only does SAS become easier to use as the user gets more familiar with its capabilities, but the customer service is excellent. Any issues with SAS and their technical team is either contacting the user via email, chat, text, WebEx, or phone. They have power users that have years of experience with SAS there to help with any issue.
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
If SAS Enterprise Guide is utilized any beginning user will be able to shorten the learning curve. This is allow the user a plethora of basic capabilities until they can utilize coding to expand their needs in manipulating and presenting data. SAS is also dedicated to expanding this environment so it is ever growing.
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
SAS probably has the most market saturation out of all of the analytics software worldwide. They are in every industry and they are knowledgable about every industry. They are always available to take questions, solve issues, and discuss a company's needs. A company that buys SAS software has a dedicated representative that is there for all of their needs.
Although nothing is perfect, SAS is almost there. The software can handle billions of rows of data without a glitch and runs at a quick pace regardless of what the user wants to perform. SAS products are made to handle data so performance is of their utmost important. The software is created to run things as efficiently as SAS software can to maximize performance.
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.
SAS is generally known for good support that's one of the main reasons to justify the cost of having SAS licenses within our organization is knowing that customer support is just a quick phone call away. I've usually had good experiences with the SAS customer support team it's one of the ways in which the company stands out in my view.
SAS has regional and national conferences that are dedicated to expanding users' knowledge of the software and showing them what changes and additions they are making to the software. There are user groups in most of the major cities that also provide multi-day seminars that focus on specific topics for education. If online training isn't the best way for the user, there is ample in-person training available.
There are online videos, live classes, and resource material which makes training very easy to access. However, nothing is circumstantial so applying your training can get tricky if the user is performing complex tasks. When purchasing software, SAS will also allocate education credits so the user(s) can access classes and material online to help expand their knowledge.
Ask as many questions you can before the install to understand the process. Since a third party does the installation your company is sort of a passanger and it is easy to get lost in the process. It also helps to have all users and IT support involved in the install to help increase the knowledge as to how SAS runs and what it needs to perform correctly.
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.
SAS is faster then both SPSS and STATA. SAS also has better models and graphs when comparing the three softwares. However, STATA and SPSS are more user friendly. It is easy to use SPSS and STATA, because a lot of it is point-click. SAS requires some training to be able to use it as effectively as possible. SAS is better with large data sets, and it is easier to analyze many data points at the same time
I think that RStudio scales pretty well based on the size of the datasets I'm using. It has multithreading capabilities unlike some other statistical analysis programs which is very useful in cutting down on time. The format of RStudio's syntax also makes it very easy to replicate regardless off the scale of the analysis and data set
It all depends on the type of SAS product the user has. Scaleability differs from product to product, and if the user has SAS Office Analytics the scaleability is quite robust. This software will satisfy the majority of the company's analytic needs for years to come. In addition, if SAS is not meeting the users needs the company can easily find SAS solutions that will.
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).