JMP Statistical Discovery Software from SAS vs. Spotfire

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
JMP Statistical Discovery Software from SAS
Score 8.3 out of 10
N/A
JMP is a division of SAS and the JMP family of products provide statistical discovery tools linked to dynamic data visualizations.
$125
per month
Spotfire
Score 8.6 out of 10
N/A
Spotfire® is a data visualization platform that utilizes predictive analytics. In addition to data viz, it includes data wrangling capabilities, predictive analytics, location analytics, and real-time streaming analytics. Spotfire® is a business unit of Cloud Software Group, formerly known as TIBCO Spotfire.
$0.99
Per Hour (Starting)
Pricing
JMP Statistical Discovery Software from SASSpotfire
Editions & Modules
Personal License
$125.00
per month
Corporate License
$1,510.00
Per Month Per Unit
TIBCO Spotfire for Amazon Web Services
$0.99
Per Hour (Starting)
TIBCO Cloud Spotfire - Consumer
$250/yr
per seat
TIBCO Cloud Spotfire - Business Author
$650/yr
per seat
TIBCO Cloud Spotfire - Analyst
$1250/yr
per seat
TIBCO Spotfire Platform
Please contact TIBCO sales
TIBCO Spotfire Cloud Enterprise
Please contact TIBCO sales
Offerings
Pricing Offerings
JMP Statistical Discovery Software from SASSpotfire
Free Trial
YesYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsFor Enterprise engagements, please contact TIBCO directly for a custom price quote.
More Pricing Information
Community Pulse
JMP Statistical Discovery Software from SASSpotfire
Considered Both Products
JMP Statistical Discovery Software from SAS
Chose JMP Statistical Discovery Software from SAS
JMP is more user-friendly, in my opinion, as it doesn't require any coding or searching for hours into cryptic folders for the analysis you want to perform. It is also very good for recording large data sets. Moreover, it is compatible with Microsoft Excel.
Spotfire
Chose Spotfire
JMP is much better suited for deep dives into one specific data set. Its ability to drill down outpaces Spotfire. JMP is also easier to learn and has more and clearer documentation than Spotfire. However, I selected Spotfire because Spotfire has much superior visualization …
Chose Spotfire
We have used Excel based visualization tools. However, it is not flexible with Excel tools. After switching to Spotfire it is almost instantaneous and we can analyze the data in various ways.
Chose Spotfire
Spotfire can handle relatively larger database and has the ability to do interactive analysis across (pool) multiple database together. In addition, the end users do not need understand the development rationale by using the developed suite for them.
Top Pros
Top Cons
Features
JMP Statistical Discovery Software from SASSpotfire
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
JMP Statistical Discovery Software from SAS
9.5
9 Ratings
12% above category average
Spotfire
8.3
299 Ratings
1% above category average
Pixel Perfect reports10.01 Ratings8.030 Ratings
Customizable dashboards9.09 Ratings9.1294 Ratings
Report Formatting Templates00 Ratings7.9258 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
JMP Statistical Discovery Software from SAS
7.6
13 Ratings
5% below category average
Spotfire
8.2
311 Ratings
1% above category average
Drill-down analysis7.813 Ratings8.3289 Ratings
Formatting capabilities6.612 Ratings7.8302 Ratings
Integration with R or other statistical packages7.810 Ratings8.3224 Ratings
Report sharing and collaboration8.113 Ratings8.5274 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
JMP Statistical Discovery Software from SAS
8.7
12 Ratings
4% above category average
Spotfire
8.3
283 Ratings
1% below category average
Publish to Web9.09 Ratings8.2228 Ratings
Publish to PDF8.712 Ratings8.6267 Ratings
Report Versioning7.01 Ratings8.018 Ratings
Report Delivery Scheduling10.01 Ratings8.4178 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
JMP Statistical Discovery Software from SAS
8.3
16 Ratings
2% above category average
Spotfire
8.2
310 Ratings
1% above category average
Pre-built visualization formats (heatmaps, scatter plots etc.)8.016 Ratings8.7306 Ratings
Location Analytics / Geographic Visualization9.013 Ratings8.4271 Ratings
Predictive Analytics7.913 Ratings8.1234 Ratings
Pattern Recognition and Data Mining00 Ratings7.68 Ratings
Access Control and Security
Comparison of Access Control and Security features of Product A and Product B
JMP Statistical Discovery Software from SAS
-
Ratings
Spotfire
8.1
250 Ratings
6% below category average
Multi-User Support (named login)00 Ratings8.7241 Ratings
Role-Based Security Model00 Ratings8.5206 Ratings
Multiple Access Permission Levels (Create, Read, Delete)00 Ratings7.8228 Ratings
Report-Level Access Control00 Ratings7.48 Ratings
Mobile Capabilities
Comparison of Mobile Capabilities features of Product A and Product B
JMP Statistical Discovery Software from SAS
-
Ratings
Spotfire
7.3
189 Ratings
9% below category average
Responsive Design for Web Access00 Ratings7.9177 Ratings
Mobile Application00 Ratings7.6126 Ratings
Dashboard / Report / Visualization Interactivity on Mobile00 Ratings7.5148 Ratings
Application Program Interfaces (APIs) / Embedding
Comparison of Application Program Interfaces (APIs) / Embedding features of Product A and Product B
JMP Statistical Discovery Software from SAS
-
Ratings
Spotfire
8.3
89 Ratings
5% above category average
REST API00 Ratings8.371 Ratings
Javascript API00 Ratings8.370 Ratings
iFrames00 Ratings8.454 Ratings
Java API00 Ratings8.257 Ratings
Themeable User Interface (UI)00 Ratings8.269 Ratings
Customizable Platform (Open Source)00 Ratings8.560 Ratings
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User Ratings
JMP Statistical Discovery Software from SASSpotfire
Likelihood to Recommend
7.4
(28 ratings)
8.6
(335 ratings)
Likelihood to Renew
10.0
(16 ratings)
8.3
(29 ratings)
Usability
10.0
(5 ratings)
8.0
(27 ratings)
Availability
10.0
(1 ratings)
9.0
(14 ratings)
Performance
10.0
(1 ratings)
7.1
(14 ratings)
Support Rating
9.2
(7 ratings)
8.7
(27 ratings)
In-Person Training
-
(0 ratings)
7.3
(52 ratings)
Online Training
7.9
(3 ratings)
8.8
(55 ratings)
Implementation Rating
9.6
(2 ratings)
8.0
(17 ratings)
Configurability
-
(0 ratings)
7.1
(3 ratings)
Ease of integration
-
(0 ratings)
7.0
(2 ratings)
Product Scalability
10.0
(1 ratings)
7.0
(4 ratings)
Vendor post-sale
-
(0 ratings)
5.0
(1 ratings)
Vendor pre-sale
-
(0 ratings)
5.0
(1 ratings)
User Testimonials
JMP Statistical Discovery Software from SASSpotfire
Likelihood to Recommend
SAS
It is perfectly suited for statistical analyses, but I would not recommend JMP for users who do not have a statistical background. As previously stated, the learning curve is exceptionally steep, and I think that it would prove to be too steep for those without statistical background/knowledge
Read full review
Spotfire
A high level of data integration is available here it supports various data sources and so on. Collaborating features allow users to give access to the dashboard and merge data analytics with other team members. It can meet the demands of both small and large size business enterprises. A customized dashboard and reports are provided to meet the specific needs and get support of extensibility through APIs and customized scripts.
Read full review
Pros
SAS
  • JMP is designed from the ground-up to be a tool for analysts who do not have PhDs in Statistics without in anyway "dumbing down" the level of statistical analysis applied. In fact, JMP operationalizes the most advanced statistical methods. JMP's design is centred on the JMP data table and dialog boxes. It is data focused not jargon-focussed. So, unlike other software where you must choose the correct statistical method (eg. contingency, ANOVA, linear regression, etc.), with JMP you simply assign the columns in a dialog into roles in the analysis and it chooses the correct statistical method. It's a small thing but it reflects the thinking of the developers: analysts know their data and should only have to think about their data. Analyses should flow from there.
  • JMP makes most things interactive and visual. This makes analyses dynamic and engaging and obviates the complete dependence on understanding p-values and other statistical concepts(though they are all there) that are often found to be foreign or intimidating.
  • One of the best examples of this is JMP's profiler. Rather than looking at static figures in a spreadsheet, or a series of formulas, JMP profiles the formulas interactively. You can monitor the effect of changing factors (Xs) and see how they interact with other factors and the responses. You can also specify desirability (maximize, maximize, match-target) and their relative importances to find factor settings that are optimal. I have spent many lengthy meetings working with the profiler to review design and process options with never a dull moment.
  • The design of experiments (DOE) platform is simply outstanding and, in fact, the principal developers of it have won several awards. Over the last 15 years, using methods broadly known as an "exchange algorithm," JMP can create designs that are far more flexible than conventional designs. This means, for example, that you can create a design with just the interactions that are of interest; you can selectively choose those interactions that are not of interest and drop collecting their associated combinations.
  • Classical designs are rigid. For example, a Box-Benhken or other response surface design can have only continuous factors. What if you want to investigate these continuous factors along with other categorical factors such as different categorical variables such as materials or different furnace designs and look at the interaction among all factors? This common scenario cannot be handled with conventional designs but are easily accommodated with JMP's Custom DOE platform.
  • The whole point of DOE is to be able to look at multiple effects comprehensively but determine each one's influence in near or complete isolation. The custom design platform, because it produces uniques designs, provides the means to evaluate just how isolated the effects are. This can be done before collecting data because this important property of the DOE is a function of the design, not the data. By evaluating these graphical reports of the quality of the design, the analyst can make adjustments, adding or reducing runs, to optimize cost, effort and expected learnings.
  • Over the last number of releases of JMP, which appear about every 18 months now, they have skipped the dialog boxes to direct, drag-and-drop analyses for building graphs and tables as well as Statistical Process Control Charts. Interactivity such as this allows analysts to "be in the moment." As with all aspects of JMP, they are thinking of their subject matter without the cumbersomeness associated with having to think about statistical methods. It's rather like a CEO thinking about growing the business without having to think about every nuance and intricacy of accounting. The statistical thinking is burned into the design of JMP.
  • Without data analysis is not possible. Getting data into a situation where it can be analyzed can be a major hassle. JMP can pull data from a variety of sources including Excel spreadsheets, CSV, direct data feeds and databases via ODBC. Once the data is in JMP it has all the expected data manipulation capabilities to form it for analysis.
  • Back in 2000 JMP added a scripting language (JMP Scripting Language or JSL for short) to JMP. With JSL you can automate routine analyses without any coding, you can add specific analyses that JMP does not do out of the box and you can create entire analytical systems and workflows. We have done all three. For example, one consumer products company we are working with now has a need for a variant of a popular non-parametric analysis that they have employed for years. This method will be found in one of the menus and appear as if it were part of JMP to begin with. As for large systems, we have written some that are tens of thousands of lines that take the form of virtual labs and process control systems among others.
  • JSL applications can be bundled and distributed as JMP Add-ins which make it really easy for users to add to their JMP installation. All they need to do is double-click on the add-in file and it's installed. Pharmaceutical companies and others who are regulated or simply want to control the JMP environment can lock-down JMP's installation and prevent users from adding or changing functionality. Here, add-ins can be distributed from a central location that is authorized and protected to users world-wide.
  • JMP's technical support is second to none. They take questions by phone and email. I usually send email knowing that I'll get an informed response within 24 hours and if they cannot resolve a problem they proactively keep you informed about what is being done to resolve the issue or answer your question.
Read full review
Spotfire
  • 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
Read full review
Cons
SAS
  • In general JMP is much better fit for a general "data mining" type application. If you want a specific statistics based toolbox, (meaning you just want to run some predetermined test, like testing for a different proportion) then JMP works, but is not the best. JMP is much more suited to taking a data set and starting from "square 1" and exploring it through a range of analytics.
  • The CPK (process capability) module output is shockingly poor in JMP. This sticks out because, while as a rule everything in JMP is very visual and presentable, the CPK graph is a single-line-on-grey-background drawing. It is not intuitive, and really doesn't tell the story. (This is in contrast with a capability graph in Minitab, which is intuitive and tells a story right off.) This is also the case with the "guage study" output, used for mulivary analysis in a Six Sigma project. It is not intuitive and you need to do a lot of tweaking to make the graph tell you the story right off. I have given this feedback to JMP, and it is possible that it will be addressed in future versions.
  • I've never heard of JMP allowing floating licenses in a company. This will ALWAYS be a huge sticking point for small to middle size companies, that don't have teams people dedicated to analytics all day. If every person that would do problem solving needs his/her own seat, the cost can be prohibitive. (It gets cheaper by the seat as you add licenses, but for a small company that might get no more than 5 users, it is still a hard sell.)
Read full review
Spotfire
  • The donut chart is I guess a powerful illustrations but I hope it should be done quite simple in Spotfire. But in Spotfire there are lots of steps involve just to build a simple donut chart.
  • Table calculation (like Row or Column Differences) should be made simple or there should be drag and drop function for Table Calculation. No need for scripting.
  • Information Link should be changed. If new columns are added to the table just refreshing the data should be able to capture the new column. No need extra step to add column
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Likelihood to Renew
SAS
JMP has been good at releasing updates and adding new features and their support is good. Analytics is quick and you don't need scripting/programming experience. It has been used organization wide, and works well in that respect. Open source means that there are concerns regarding timely support. Cheap licensing and easy to maintain.
Read full review
Spotfire
-Easy to distribute information throughout the enterprise using the webplayer. -Ad hoc analysis is possible throughout the enterprise using business author in the webplayer or the thick client. -Low level of support needed by IT team. Access interfaces with LDAP and numerous other authentication methods. -Possible to continually extend the platform with JavaScript, R scripts, HTML, and custom extensions. -Ability to standardize data logic through pre-built queries in the Information Designer. Everyone in the enterprise is using the same logic -Tagging and bookmarking data allows for quick sharing of insights. -Integration with numerous data sources... flat files, data bases, big data, images, etc. -Much improved mapping capability. Also includes the ability to apply data points over any image.
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Usability
SAS
The overall usability of JMP is extremely good. What I really love about it is its ability to be useable for novices who have no coding experience, which is not the case with most other, similar, programs. It can output a fast and easy analysis without too much prior coding or statistical knowledge.
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Spotfire
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
SAS
No answers on this topic
Spotfire
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
SAS
No answers on this topic
Spotfire
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
SAS
Support is great and give ease of contact, rapid response, and willingness to 'stick to the task' until resolution or acknowledgement that the problem would have to be resolved in a future build. Basically, one gets the very real sense that another human being is sensitive to your problems - great or small.
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Spotfire
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
SAS
No answers on this topic
Spotfire
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
SAS
I have not used your online training. I use JMP manuals and SAS direct help.
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Spotfire
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
SAS
No answers on this topic
Spotfire
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
SAS
It is great because it has UI menus but it costs money whereas the other programs are free. That makes it ideal for beginners but I think that RStudio and Python are going to make someone a lot more marketable for future opportunities since most companies won't pay for the software when there is a great free option.
Read full review
Spotfire
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 custom javascript visaualizations, which neither Tableau or Power BI has. Tableau and Power BI are likely only superior to Spotfire with respect to embedded analysis on a website.
Read full review
Scalability
SAS
No answers on this topic
Spotfire
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
SAS
  • ROI: Even if the cost can be high, the insights you get out of the tool would definitely be much more valuable than the actual cost of the software. In my case, most of the results of your analysis were shown to the client, who was blown away, making the money spent well worth for us.
  • Potential negative: If you are not sure your team will use it, there's a chance you will just waste money. Sometimes the IT department (usually) tries to deploy a better tool for the entire organization but they keep using the old tool they are used too (most likely MS Excel).
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Spotfire
  • It is costly, so not suitable for small scale implementations.
  • Dashboards are as good as the developer, so need experience to get most out of it
  • You need to be on Spotfire 11 at least to implement out of the box visualizations
  • Integration with Python and R is a game changer, it comes very handy to onboard data scientists without much hassle
  • performance is exceptionally well.
  • Secure
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ScreenShots

JMP Statistical Discovery Software from SAS Screenshots

Screenshot of Graph Builder.Screenshot of Design of ExperimentsScreenshot of Hierarchical and KMeans clustering are available from the Multivariate platform.Screenshot of Scatterplot Multivariate AnalysisScreenshot of Survey Analysis

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