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.
N/A
Mathematica
Score 8.2 out of 10
N/A
Wolfram's flagship product Mathematica is a modern technical computing application featuring a flexible symbolic coding language and a wide array of graphing and data visualization capabilities.
$1,520
per year
Pricing
Spotfire
Wolfram Mathematica
Editions & Modules
No answers on this topic
Standard Cloud
$1,520
per year
Standard Desktop
$3,040
one-time fee
Standard Desktop & Cloud
$3,344
one-time fee
Mathematica Enterprise Edition
$8,150.00
one-time fee
Offerings
Pricing Offerings
Spotfire
Mathematica
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
For Enterprise engagements, contact Spotfire directly for a custom price quote.
Discounts available for students and educational institutions. The Network Edition reduce per-user license costs through shared deployment across any number of machines on a local-area network.
More Pricing Information
Community Pulse
Spotfire
Wolfram Mathematica
Considered Both Products
Spotfire
Verified User
Anonymous
Chose Spotfire
No experience with the tools in the list above other than Spotfire.
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 …
Projektspezialist bei Steffen Jäschke EinzUnt Physik, Berechnungen
Chose Mathematica
There is no other alternative that Maple from Maplesoft all over. There are other systems for mCAx that do not offer the richness and coverage of mathematical features. For example Matlab that restricts inself to matrice calculation and only the the right set of addon library …
Well, Mathematica is free at my university. As a graduate student, you can download and install Mathematica in your device after log in through your university email. Second, it has very nice platform. You can use Mathematica for many data analysis such as plotting, integration …
Matlab is an excellent tool, but it can't handle analytic manipulations in algebra, calculus and differential equations. Matlab is superior when it comes to a less steep learning curve. In terms of using only one tool for analytic and numerical calculations, Mathematica wins. …
Mathematica is good solution in some cases but doesn't perform well in other regions. Mathematica is good in solving mathematical problems but not performs well in machine learning areas. I would suggest to use TensorFlow or Keras for machine learning. Also it performs good for …
The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
We have evaluated and are using in some cases the Python language in concert with the Jupyter notebook interface. For UI, we using libraries like React to create visually stunning visualizations of such models.
Mathematica compares favorably to this alternative in terms of …
We selected Wolfram Mathematica as it offers lot of functionality that other products like MATLAB or sageMath do not have. And it also has advantages on the feature that it does share in common with other tools like sageMath, MATLAB etc. It is more powerful than MATLAB. It …
I think IBM Watson analytics is good alternative to Wolfram Mathematica. A few advantages of Mathematica over IBM Analytics is that Mathematica comes with a lot of inbuilt things like neural networks, predictive analysis geometry. And IBM analytics does not show the step by …
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.
We are the judgement that Wolfram Mathematica is despite many critics based on the paradigms selected a mark in the fields of the markets for computations of all kind. Wolfram Mathematica is even a choice in fields where other bolide systems reign most of the market. Wolfram Mathematica offers rich flexibility and internally standardizes the right methodologies for his user community. Wolfram Mathematica is not cheap and in need of a hard an long learner journey. That makes it weak in comparison with of-the-shelf-solution packages or even other programming languages. But for systematization of methods Wolfram Mathematica is far in front of almost all the other. Scientist and interested people are able to develop themself further and Wolfram Matheamatica users are a human variant for themself. The reach out for modern mathematics based science is deep and a unique unified framework makes the whole field of mathematics accessable comparable to the brain of Albert Einstein. The paradigms incorporated are the most efficients and consist in assembly on the market. The mathematics is covering and fullfills not just education requirements but the demands and needs of experts.
Mathematica is incompatible with other systems for mCAx and therefore the borders between the systems are hard to overcome. Wolfram Mathematica should be consider one of the more open systems because other code can be imported and run but on the export side it is rathe incompatible by design purposes. A better standard for all that might solve the crisis but there is none in sight. Selection of knowledge of what works will be in the future even more focussed and general system might be one the lossy side. Knowledge of esthetics of what will be in the highest demand in necessary and Wolfram is not a leader in this field of science. Mathematics leves from gathering problems from application fields and less from the glory of itself and the formalization of this.
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.
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.
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.
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.
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.
Wolfram Mathematica is a nice software package. It has very nice features and easy to install and use in your machine. Besides this, there is a nice support from Wolfram. They come to the university frequently to give seminars in Mathematica. I think this is the best thing they are doing. That is very helpful for graduate and undergraduate students who are using Mathematica in their research.
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.
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
The ability to manipulate algebraic expressions, nested lists, and data structures in Mathematica was unequalled when I first did the comparison. Since then, I've stuck with Mathematica mostly because it's "the tool I know."
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,
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.
Mathematica is our "go to" environment for developing solutions for our clients, so I suppose you could say that it is solely responsible for our revenues. On occasion we do use other platforms but Mathematica is a core component of our offer to clients.