Posit, formerly RStudio, is a modular data science platform, combining open source and commercial products.
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Spotfire
Score 8.1 out of 10
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Spotfire, formerly known as TIBCO Spotfire, is a visual data science platform that combines visual analytics, data science, and data wrangling, so users can analyze data at-rest and at-scale to solve complex industry-specific problems.
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Pricing
Posit
Spotfire
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Pricing Offerings
Posit
Spotfire
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
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No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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For Enterprise engagements, contact Spotfire directly for a custom price quote.
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Community Pulse
Posit
Spotfire
Considered Both Products
Posit
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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 …
Spotfire has an extremely large and dynamic range of visual analysis tools that can be catered for most issues or projects to create a custom analytics dashboard when compared to other tools I've used. It's multitude of available database connections allow for most …
Spotfire is stronger than other tools to built complex metrics within the tool, without needs of etl updates and query changing. It has lots of useful visualizations to deep dive data and give interesting analysis to business users. Moreover, with some studies and tests, you …
Although Spotfire has a longer learning curve, it has proven to be more practical and impactful than Tableau. We had only evaluated other tools at a high level initially, and were surprised to hear the success stories of companies moving from Tableau to Spotfire. We have found …
Because of Spotfire's robust features and capabilities, I chose it as my
preferred software. Spotfire's greater overall performance and
scalability set it apart from other software solutions. It can handle
Spotfire is appropriate for every organization of any size because it can be a recipient of data for better decision-making. Being a robust development platform for creating reports and dashboards, creating a new Spotfire dashboard is relatively simple. Developers can create …
Spotfire is more suited for manufacturing industries with regards the huge data to process to make relevant decision that use big data for making decisions, besides this Spotfire supports more and excels at Availability & Scalability, Data Sources Connectivity and Deployment …
I choose Spotfire because of the following - custom visual using JavaScript - on the fly chart property update using iron python - easy report Deployment and update -easy to manage user access via so or ldap - best report data Extraction -mix data sources -custom data load …
Spotfire is significantly ahead of both products from an ETL and data ingestion capability. Spotfire also has substantially better visualizations than Power BI, and although the native visualizations aren't as flexible in Tableau, Spotfire enables users to create completely …
Spotfire's key strength les in extent of customization possible and it's inherent Data Analytics capabilities. With in-memory and in-database analysis capabilities, it comes out as a high performance and high efficiency BI solution. Adding to it, Spotfire integrates the …
Easy to use and is a very flexible tool. Great to have multiple services. Find it to be a trusted platform. The ability to add Iron Python scripts and include code snippets is very useful. Like the style of the created views.
I find both Microsoft Power BI and Spotfire very easy to use. I would rate them on par with each other. There isn’t much to differentiate them. Maybe the learning curve on Spotfire is a bit steeper than Microsoft Power BI.
Augmented AI with Spotfire is very useful for data virtualization. Since data visualization is a quick and very easy way to convey our information. This software makes it easier with its interactive way of presenting data in charts, graphs, and 3D forms.
It provides all tools along with in-built apps for analysis and generating reports, metrics, charts, and graphs. Comes with appropriate costing model at least for an average size organization
Spotfire is the best application for power users by virtue of its wide variety of visualizations, incorporated analytics, superior data canvas, and ability to integrate code such as R or Python. The learning curve is steeper and the menus are Windows 7 once you are past some …
The only other tool we use in my course is Tableau. Tableau is very popular regionally (Omaha, NE), runs locally on Mac and PC, is free for students and faculty, and has a web outlet for sharing. It also plays well with AWS. For these reasons, we use it as the primary …
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.
Spotfire was used to look at a large data set of an in process manufacturing step. The data visualization was set up to look at yield as a function of several inputs (chemical / equipment / operator). After only a short analysis it was immediately obvious that there was a 5% yield discrepancy based on the operator using the equipment. The operators were retrained and the yield gap was eliminated.
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.
They should have a lower price point for users to access the analyst version who don't require advanced capabilities. For example, a lower price if users just need to do some basic slicing and dicing with their data and not have to the data science functionality (ie. K-means clustering, regression modeling, classification modeling, etc.).
Currently, you can't change the font type/color on the axis, which I'm sure will eventually be available in the future as they have a Spotfire Ideas portal that they're fairly responsive to and act on. I guess at the end of the day, it's about the data and what insights you get from it.
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.
It's a very powerful tool that allows for a myriad of customizations within the analysis files themselves, particularly with the custom expression functionality. There have been some great strides with the quality of the visualization options (which were not great to begin with) and I hope to see more improvements made as the product gets updated.
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
Basic tasks like generating meaningful information from large sets of raw data are very easy. The next step of linking to multiple live data sources and linking those tables and performing on the fly analysis of the imported data is understandably more difficult.
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
Even though, it's a rather stable and predictable tool that's also fast, it does have some bugs and inconsistencies that shut down the system. Depending on the details, it could happen as often as 2-3 times a week, especially during the development period.
Generally, the Spotfire client runs with very good performance. There are factors that could affect performance, but normally has to do with loading large analysis files from the library if the database is located some distance away and your global network is not optimal. Once you have your data table(s) loaded in the client application, usually the application is quite good performance-wise.
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.
Support has been helpful with issues. Support seems to know their product and its capabilities. It would also seem that they have a good sense of the context of the problem; where we are going with this issue and what we want the end outcome to be.
The instructor was very in depth and provided relevant training to business users on how to create visualizations. They showed us how to alter settings and filter views, and provided resources for future questions. However, the instructor failed to cover data sources, connecting to data, etc. While it was helpful to see how users can use the data to create reports, they failed to properly instruct us on how to get the dataset in to begin with. We are still trying to figure out connections to certain databases (we have multiple different types).
The online training is good, provides a good base of knowledge. The video demonstrations were well-done and easy to follow along. Provided exercises are good as well, but I think there could be more challenging exercises. The training has also gone up in price significantly in the last 3 years (in USD, which hurts us even more in Canada), and I'm not sure it is worth the money it now costs (it is worth how much it cost 3 years ago, but not double that.)
The original architecture I created for our implementation had only a particular set of internal business units in mind. Over the years, Spotfire gained in popularity in our company and was being utilized across many more business units. Soon, its usage went beyond what the original architectural implementation could provide. We've since learned about how the product is used by the different teams and are currently in the middle of rolling out a new architecture. I suggest:
Have clearly defined service level agreements with all the teams that will use Spotfire. Your business intelligence group might only need availability during normal working hours, but your production support group might need 24/7 availability. If these groups share one Spotfire server, maintenance of that server might be a problem.
Know the different types of data you will be working with. One group might be working with "public" data while another group might work with sensitive data. Design your Library accordingly and with the proper permissions.
Know the roles of the users of Spotfire. Will there only be a small set of report writers or does everyone have write access to the Library?
ALWAYS add a timestamp prompt to your reports. You don't want multiple users opening a report that will try and pull down millions of rows of data to their local workstations. Another option, of course, is to just hard code a time range in the backing database view (i.e. where activity_date >= sysdate - 90, etc.), but I'd rather educate/train the user base if possible.
This probably goes without saying, but if possible, point to a separate reporting database or a logical standby database. You don't want the company pounding on your primaries and take down your order system.
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.
Spotfire is appropriate for every organization of any size because it can be a recipient of data for better decision-making. Being a robust development platform for creating reports and dashboards, creating a new Spotfire dashboard is relatively simple. Developers can create highly customized dashboards using the tools it provides. I will recommend this software to others
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
In an enterprise architecture, if Spotfire Advanced Data services(Composite Studio),data marts can be managed optimally and scalability in a data perspective is great. As the web player/consumer is directly proportional to RAM, if the enterprise can handle RAM requirement accomodating fail over mechanisms appropraitely, it is definitely scalable,
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).
Spotfire really helped a lot of people in terms of analysis. It eliminates data analysis in excel. Because even underlying data you can explore it in Spotfire.
Spotfire helps data analysts to investigate data and also help analysts solve inconsistency of data.
Spotfire helps data analysts in building great dashboard that provide insights to users to make decisions to drive revenue and manage the churn.