Gephi vs. Spotfire

It is well suited for projects that are more discovery related. If this is a one-time project that we create a visual for, this would definitely make sense to use. If this is an ongoing analysis (monthly for example), we might look to another software that we would be able to automate a little further in how the visualization comes together

Incentivized

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.

Incentivized

• In comparison to other tools such as GraphWiz or Circos, Gephi comes with an intuitive, easy-to-use interface that makes it easy to load your data, and quickly start building all sorts of different graphs. There's absolutely no code that needs to be written for either loading or modeling. And without downloading additional plug-ins, Gephi ships with quite a few standard graph models, as well as some "fun" extras such as the Sierpinski triangle, and a variety of force atlas types.
• Most of the layout types (maybe all) are highly configurable, which can make for extremely customized and unique displays of your data. Again, none of this requires the user to write any code. That said, it is possible to script custom functionality for your models, or even update the Java source code yourself, if you feel like getting technical. Gephi builds are available on GitHub, and the developers encourage people to contribute ideas, improvements, and plug-ins.
• There's a plug-in for Gephi that allows for streaming data to update your model. This essentially allows you to create near realtime graphs of your data in motion. This plug-in was by far the biggest reaston we invested time in the product; to create animated data visualizations without exhaustive hours in development.

• 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

Incentivized

• I (and many others) have had to expand Gephi's memory manually by experimenting with the configuration file. I'm glad it's possible, but it should be easier.
• Gephi sometimes crashes inexplicably and loses your work, so I have developed a habit of explicitly exporting versions of my graphs as csv's, but I think this should be handled automatically in Gephi.
• Because it is prone to crash, ideally, Gephi would help the user manage his/her use, by estimating processing and memory for very large tasks and prompting the user to confirm their requests before executing. Instead, I just tend to avoid certain functions.

• 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

Incentivized

While Gephi isn't perfect, it's a powerful tool for mathematical graph modelling that's hard to find in other products, particularly by way of its interface. It grants non-software developers access to a point-and-click way of creating accurate, beautiful visualizations that would normally take hours in other applications. The fact that it allows for live streaming data is also something that's hard to come by, at least for visualization software

-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.

Gephi is very intuitive and the fact that it shows its process helps the user understand what's going on. However, the animation features can really slow it down and there isn't a way to shut them off. Furthermore, the failures on saving mean you frequently have to start over. These problems disrupt the workflow and can be frustrating.

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.

Incentivized

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.

Incentivized

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).

Incentivized

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.)

Incentivized

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.

The interactivity in Gephi and the quality of the output figures are impressive. However, the selling point was the fact that we were able to link Gephi into our pipeline using Java's interface. Other products were less customizable and lacking of the sophistication Gephi provided without too much pain during the liking process.

Incentivized

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.

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,

Incentivized

• I have only used the product for education purposes. I will not be the best person to provide details about ROI and business efficiency and customer service. I was personally very excited about the tool and am continuing my work on the tool.

• 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

Incentivized