Apache Spark vs. SAP Crystal

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.

Incentivized

Generation of templated reports is the strong suit of SAP Crystal. Allows users to change formats in templates bases on requirement with minimal effort. Automated report delivery requires the user to be aware of sql which cannot be expected from all users. Should support more document export formats and improve the UI for SAP B1 Users

Incentivized

• Rich APIs for data transformation making for very each to transform and prepare data in a distributed environment without worrying about memory issues
• Faster in execution times compare to Hadoop and PIG Latin
• Easy SQL interface to the same data set for people who are comfortable to explore data in a declarative manner
• Interoperability between SQL and Scala / Python style of munging data

Incentivized

• Crystal Reports allows us to create a consistent template for all of our reports.
• Crystal Reports and Server allows us to house a repository for all of our reports to make them easy to find and update when necessary.
• Crystal Reports can connect to a wide variety of data sources.
• Crystal Reports can be a little daunting when first implementing. There are a lot of nuances in learning how to truly master this software and it can be frustrating at times.

Incentivized

• Memory management. Very weak on that.
• PySpark not as robust as scala with spark.
• spark master HA is needed. Not as HA as it should be.
• Locality should not be a necessity, but does help improvement. But would prefer no locality

Incentivized

• The export of reports to Excel is very cumbersome and the results are difficult to format.
• The design of reports and the graphical features (e.g. charts) feel quite rigid.
• The learning curve for a non-programmer is incredibly steep, making Crystal a specialty tool.

Incentivized

Capacity of computing data in cluster and fast speed.

We have been using this product for so many years and it has truly become a cornerstone to our business processes when it comes to developing and distributing information via reports. We currently have over 500 reports developed to date over about 30 systems and that will continue to grow as user needs change.

If the team looking to use Apache Spark is not used to debug and tweak settings for jobs to ensure maximum optimizations, it can be frustrating. However, the documentation and the support of the community on the internet can help resolve most issues. Moreover, it is highly configurable and it integrates with different tools (eg: it can be used by dbt core), which increase the scenarios where it can be used

Incentivized

Crystal is very robust, but not always easy to use. It create wonderful looking reports, and so deserves a high rating. However, I have to take a couple of points off for the simple fact that I cannot hand it to a user and expect them to be able to do development with it.

Incentivized

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.

The support community can be difficult to navigate. I've also run into issues with my login. The SAP system has a bizarre mechanism for validating users that requires users to have what is called an S-ID. A basic ID may not give you access to all the features in the portal. The limitation may include not being able to perform a simple task like downloading patches and updates. This isn't a big deal for single user license but for teams it can be a pain.

Incentivized

Trainer was patient and thorough in going through the basics and willing to answer questions by email after the initial training

Incentivized

Just like any other implementation: When designing the differing reports, get end users' input, make sure to design the reports so that they display the information that the company requires, in the best and clearest way possible.

Test, test, test, revise when needed, and, particularly, do sufficient training so users are comfortable using Crystal Reports!

Incentivized

Spark in comparison to similar technologies ends up being a one stop shop. You can achieve so much with this one framework instead of having to stitch and weave multiple technologies from the Hadoop stack, all while getting incredibility performance, minimal boilerplate, and getting the ability to write your application in the language of your choosing.

Incentivized

Crystal reports is useful in case we want to import data from data base . We can write queries in it but Google Charts require to be implemented in our application using code so crystal reports is better than Google Charts.

Incentivized

• Business leaders are able to take data driven decisions
• Business users are able access to data in near real time now . Before using spark, they had to wait for at least 24 hours for data to be available
• Business is able come up with new product ideas

Incentivized

• It is a decent buy for specific departments in terms of reporting capabilities but updates and cost (frequent) demands are higher with the benefits offered.
• So long as the requirements are not ever changing, with scheduling functionality, it's a handsome tool.

Incentivized