JMP vs. Spotfire

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
JMP
Score 9.2 out of 10
N/A
JMP® is statistical analysis software with capabilities that span from data access to advanced statistical techniques, with click of a button sharing. The software is interactive and visual, and statistically deep enough to allow users to see and explore data.
$1,320
per year per user
Spotfire
Score 8.1 out of 10
N/A
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
Pricing
JMPSpotfire
Editions & Modules
JMP
$1320
per year per user
No answers on this topic
Offerings
Pricing Offerings
JMPSpotfire
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsBulk discounts available.For Enterprise engagements, contact Spotfire directly for a custom price quote.
More Pricing Information
Community Pulse
JMPSpotfire
Features
JMPSpotfire
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
JMP
-
Ratings
Spotfire
7.2
Ratings
15% below category average
Connect to Multiple Data Sources00 Ratings7.80 Ratings
Extend Existing Data Sources00 Ratings7.40 Ratings
Automatic Data Format Detection00 Ratings7.80 Ratings
MDM Integration00 Ratings6.00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
JMP
-
Ratings
Spotfire
9.1
Ratings
8% above category average
Visualization00 Ratings9.00 Ratings
Interactive Data Analysis00 Ratings9.20 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
JMP
-
Ratings
Spotfire
7.4
Ratings
10% below category average
Interactive Data Cleaning and Enrichment00 Ratings7.20 Ratings
Data Transformations00 Ratings8.00 Ratings
Data Encryption00 Ratings7.00 Ratings
Built-in Processors00 Ratings7.50 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
JMP
-
Ratings
Spotfire
7.6
Ratings
10% below category average
Multiple Model Development Languages and Tools00 Ratings7.50 Ratings
Automated Machine Learning00 Ratings8.50 Ratings
Single platform for multiple model development00 Ratings7.60 Ratings
Self-Service Model Delivery00 Ratings6.70 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
JMP
-
Ratings
Spotfire
7.4
Ratings
14% below category average
Flexible Model Publishing Options00 Ratings7.80 Ratings
Security, Governance, and Cost Controls00 Ratings7.00 Ratings
Best Alternatives
JMPSpotfire
Small Businesses
IBM SPSS Statistics
IBM SPSS Statistics
Score 7.8 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.4 out of 10
Medium-sized Companies
Alteryx Platform
Alteryx Platform
Score 8.9 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Dataiku
Dataiku
Score 7.6 out of 10
Posit
Posit
Score 10.0 out of 10
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User Ratings
JMPSpotfire
Likelihood to Recommend
9.0
(0 ratings)
8.4
(0 ratings)
Likelihood to Renew
10.0
(0 ratings)
9.6
(0 ratings)
Usability
8.0
(0 ratings)
8.0
(0 ratings)
Availability
10.0
(0 ratings)
9.0
(0 ratings)
Performance
10.0
(0 ratings)
7.1
(0 ratings)
Support Rating
9.2
(0 ratings)
8.7
(0 ratings)
In-Person Training
-
(0 ratings)
8.3
(0 ratings)
Online Training
7.9
(0 ratings)
9.0
(0 ratings)
Implementation Rating
9.6
(0 ratings)
8.4
(0 ratings)
Configurability
-
(0 ratings)
7.1
(0 ratings)
Ease of integration
-
(0 ratings)
7.0
(0 ratings)
Product Scalability
10.0
(0 ratings)
7.0
(0 ratings)
Vendor post-sale
-
(0 ratings)
5.0
(0 ratings)
Vendor pre-sale
-
(0 ratings)
5.0
(0 ratings)
User Testimonials
JMPSpotfire
Likelihood to Recommend
Many organizations have seen their analytical capabilities, and the results from them, plateau. Of these, we've observed, that most of them didn't appreciate that they could do (even) better. These companies should definitely consider JMP. Any company that is research-based can benefit from accelerating their research, learning more in less time, effort and cost, with JMP's tools. Basically, any organization that is hungry enough for improvement to seek out better ways is suitable for JMP. Those who are happy with their current performance are not likely to consider the changes, though they were not major impediments by our clients, required.
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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.
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Pros
  • Graphs are more detail-oriented and contain statistical inferences.
  • Everything is drag and drop. Pretty much easy to use and handle and also to learn.
  • Importing and exporting the results are easy and they can be attached with any other tool for processing.
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  • It has the best coding integration (python, R) of any BI product
  • The ability to work with very large datasets (10 mil+) is better than competitors
  • Export options are more complete and have better functionality
  • The data canvas is the best tool to join and transform data vs. competitors
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Cons
  • Loading a large amount of data is very tedious as it takes a lot of time and it crashes very frequently.
  • I dislike the limited options they have in terms of statistical models or analysis tools.
  • Variable value designation is a big problem in JMP, the software fails to recognize the type of data when it comes to the numeric value.
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  • 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.
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Likelihood to Renew
I've mentioned this earlier, but the licensing agreements are very prohibitive. I work with a company where my role has become less and less doing my own analytics and more and more trying to help other people in that role. As we are bringing more people "up to speed" it's hard to justify licenses for 2-3 people when they aren't full time, Six Sigma black belts just looking at stats all day. A floating license option would make this a no-brainer, since these people could continue their other work and add JMP usage as they grow their skills, but this is not something JMP/SAS has offered.
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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.
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Usability
The GUI interface makes it easier to generate plots and find statistics without having to write code. The JSL scripting is a bit of a steep learning curve but does give you more ability to customize your analysis. Overall, I would recommend JMP as a good product for overall usability.
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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.
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Reliability and Availability
No answers on this topic
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.
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Performance
No answers on this topic
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.
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Support Rating
The helpful tips are great for new users. I am always able to find solutions to a tool I am working with through the hep section. And my area has a users group that meets each quarter to share ideas and view upcoming JMP revisions.
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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.
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In-Person Training
No answers on this topic
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).
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Online Training
I have not used your online training. I use JMP manuals and SAS direct help.
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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.)
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Implementation Rating
No answers on this topic
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.
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Alternatives Considered
We actually use both JMP and IBM SPSS, but I think JMP's complexity lends itself to more in-depth statistical analyses. SPSS is designed for that as well, but we tend to use it more for quicker analyses, and we have found that JMP is far more powerful.
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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
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Scalability
No answers on this topic
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,
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Return on Investment
  • JMP has resulted in literally millions of dollars in ROI due to identification of correctable errors.
  • Use of JMP control charts JMP has greatly simplified and improved interpretation of Lean, FMEA, and PDSA type analyses.
  • Use of JMP has enable the testing and subsequent selection of 'best practices' saving uncounted hours in false starts based on 'collective experience'.
  • The down side is that JMP is not a 'magic box', one still has to take care in applying the tools properly. Moreover, time-consuming approaches using JMP may still be the 'order of the day', because the service (even power user) is unaware of significant shortcuts available for free on the JMP community website.
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  • 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.
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ScreenShots

JMP Screenshots

Screenshot of in JMP, how all graphical displays and the data table are linked.Screenshot of a few designed experiments, for more understanding and maximum impact. Users can understand cause and effect using statistically designed experiments — even with limited resources.Screenshot of an example of Predictive Modeling in JMP Pro's Prediction Profiler, used to build better models for more confident decision making.Screenshot of example outputs, built with tools designed for quality and reliability.

Spotfire Screenshots

Screenshot of Smart Visual AnalyticsScreenshot of Geospatial AnalyticsScreenshot of Intelligent Data WranglingScreenshot of Point-and-click Data ScienceScreenshot of Real-time Streaming Analytics