Jaspersoft commercial edition is an embedded business intelligence suite designed to be built-into SaaS products as an integrated reporting engine. It provides reports and dashboards for customer-facing applications without requiring app developers to build their own reporting engine.
N/A
Pricing
Apache Spark
Jaspersoft
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache Spark
Jaspersoft
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
—
Jaspersoft offers flexible pricing for ISVs and SaaS per customer or by CPU core.
Well suited: To most of the local run of datasets and non-prod systems - scalability is not a problem at all. Including data from multiple types of data sources is an added advantage. MLlib is a decently nice built-in library that can be used for most of the ML tasks. Less appropriate: We had to work on a RecSys where the music dataset that we used was around 300+Gb in size. We faced memory-based issues. Few times we also got memory errors. Also the MLlib library does not have support for advanced analytics and deep-learning frameworks support. Understanding the internals of the working of Apache Spark for beginners is highly not possible.
It is well suited for the fact of scalability itself and the breadth of features this application has in order to make the migration from legacy systems to the newer different versions more seamless and effective. Data integrity and security are the main aspects of this tool which does not lose their value when doing day-to-day operations for data mapping.
TIBCO Jaspersoft allows you to embed reports into your own application, which gives users the feeling they are using a single product.
TIBCO Jaspersoft Studio allows for more advanced report development, such as adding subreports, drilldown to detail reports, images, page headers, page footers, maps, and more.
TIBCO's Jaspersoft Domain Designer is very easy to use and navigate.
One of the issues we found during our implementation was that the reporting software would work faster for certain data sources and not the others. Extracting CSVs and XML was slower in comparison to JSON in our experience.
Jaspersoft Studio was the main IDE we used for development. Built atop the Eclipse IDE, we found that the tool was really resource intensive and generally take long time to initialize.
JasperSoft has been amazing. It is well documented, fast, and transparent in how it functions. We have been very confident in JasperSoft in every aspect of our business and offerings where we've used it. On top of that, their improvements to the product have been fantastic. I am really looking forward to seeing where they take their product and how we can leverage that to please our clients
The only thing I dislike about spark's usability is the learning curve, there are many actions and transformations, however, its wide-range of uses for ETL processing, facility to integrate and it's multi-language support make this library a powerhouse for your data science solutions. It has especially aided us with its lightning-fast processing times.
I think it's a tool well suited for a software developer. Others with less coding skills could struggle somewhat with the tool. I find java a little unforgiving as a language for expressions and not very user friendly for the technically dis-inclined. Sometimes the numeric conversions cause issues (who knew that 0 and 0.0 would cause different things to happen). Previous experience with a reporting tool that used visual basic for its' expressions that I found much simpler to use. On the other hand, java is so widespread, you can easily google the syntax to accomplish what you need to do.
1. It integrates very well with scala or python. 2. It's very easy to understand SQL interoperability. 3. Apache is way faster than the other competitive technologies. 4. The support from the Apache community is very huge for Spark. 5. Execution times are faster as compared to others. 6. There are a large number of forums available for Apache Spark. 7. The code availability for Apache Spark is simpler and easy to gain access to. 8. Many organizations use Apache Spark, so many solutions are available for existing applications.
They have a great customer support ticketing system in which they always respond same-day. They offer conference calls with srcreensharing as well in order to better understand your issues.
I wish that the lower level support access came with more than just 12 cases per year though as this makes us less likely to reach out for questions on things that we then instead try to solve ourselves which results in loss of time in trying to acquire new features and or solve a problem.
It did the job of getting us to our deadline we set for ourselves for initial launch. The customer we launched the product for was also there to learn about it at the same in order to better understand the capabilities. This helped greatly so that the customer was on the same page on what was possible when using jaspersoft. I think most people would not want their customers aware the product they are using is third-party but in this case it was a new experience for us both and so as we learned more about jaspersoft, we both had better communication on what the future road map was for their business needs in BI.
Resources available in the TIBCO Knowledge Base are covering almost everything. They are well organized, and covering almost every possibility. There is always the change to get back to the TIBCO support or to the dedicated Customer Success Manager whenever something very specific or bound to a customization is not covered.
Having just completed an upgrade to the latest version of Jaspersoft, I am happy to say their support was very good. There were a couple of small challenges which were not easily resolved, but they were primarily related to the fact that we had skipped updates for a couple of versions. The current update procedures assumed we were upgrading from the prior latest version (6.4) to to the new version (7.1).
All the above systems work quite well on big data transformations whereas Spark really shines with its bigger API support and its ability to read from and write to multiple data sources. Using Spark one can easily switch between declarative versus imperative versus functional type programming easily based on the situation. Also it doesn't need special data ingestion or indexing pre-processing like Presto. Combining it with Jupyter Notebooks (https://github.com/jupyter-incubator/sparkmagic), one can develop the Spark code in an interactive manner in Scala or Python
When looking at the different features of these reporting engines, and what we were going to be using it for, the answer seemed clear. Jasper offered exactly what we were looking for, and did so for a price that we were happy with. For a scalable, feature-rich reporting engine that doesn't break the bank, Jaspersoft is the way to go.
Faster turn around on feature development, we have seen a noticeable improvement in our agile development since using Spark.
Easy adoption, having multiple departments use the same underlying technology even if the use cases are very different allows for more commonality amongst applications which definitely makes the operations team happy.
Performance, we have been able to make some applications run over 20x faster since switching to Spark. This has saved us time, headaches, and operating costs.
When we demo our Jaspersoft environment to potential clients, their eyes light up and they sit up in their chairs a bit more. A lot of our meetings have ended with with the client very interested in our product due to Jaspersoft.
Our existing clients have been very satisfied with the adhoc features of Jaspersoft. We've been able to provide them better access to their data on their terms instead of ours. Of course this turns into a huge win for us.
We've always used SQL Server Reporting Services to deliver our reports to our clients. Converting to Jaspersoft has allowed us to generate the reporting layer that our clients demand. They no longer feel like they are settling for what we offer.
