Apache Spark vs. SAP Analytics Cloud

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

SAP Analytics Cloud is great for big companies that want advanced data analysis and planning, especially when they need to work together in real-time or when people need to access data on their phones. It's like a super tool for predicting future trends in industries like retail or finance. SAC also works well for companies that use different types of computer systems because it can easily connect them. But, for small businesses that only need basic reports or don't have a lot of technical resources, a simpler tool might be better. If a company doesn't always have a good internet connection or if they're just starting with analytics, there might be other tools that work better.

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

• It makes it easier yo analyse order and related records easily.
• We can easily maintain and track the performance of employees in organisation.
• Can easily track various aspects for the growth of an organisation thus allowing real time analysis and tracking of organisation's growth and performance.

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

• Complexity in Data Modeling
• SAC supports various data sources, but improvements in the ease of connecting to and integrating with certain data repositories, especially non-SAP databases, would enhance the platform's versatility and integration capabilities.
• An offline mode for SAC could be valuable for users who need to access and analyze data without an internet connection. Additionally, optimizing performance for large datasets and complex visualizations would contribute to a smoother user experience.

Incentivized

Capacity of computing data in cluster and fast speed.

There’s no doubt I will renew SAP Analytics Cloud. It is the most vital tool in our organization that makes it seamless to make rapid business decisions by collecting, modeling and visualizing data in real-time.

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

Considering the feedback and improvements made over time, users often rate SAP Analytics Cloud's usability in the range of 7 to 9 out of 10. Positive aspects include its integration capabilities, collaborative features, and the ability to create visually appealing dashboards. Some users, however, may note a learning curve or desire additional customization options.

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.

Since the implementation stage, the support team has been very helpful and assisting. Even in the later stages, the tech team had quite a rapid response. In general, SAP has provided us with great customer support, let it be for a specific product of SAP or for integration of different modules.

Incentivized

Good videos and reference material available in SAP Portal.

Incentivized

SAC is a simple solution ad it works fine when connecting it to other SAP tools. On the other hand, connecting it to third party solutions brings difficulties when there's no previous design and the objetives are not clear. It is really important to integrate Business users from the start to provide with valuable business insights

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

SAP is a product/solution that contains extra capabilities that might be considered an enhancement; SAP Analytics Cloud models are based on a huge data collection, and numerous models can be integrated. When coupled with different SAP systems, Analytics Cloud has a common dataset architecture; this software also includes improved analytics capabilities.

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

• In general, SAC is a comprehensive analytics platform that offers a range of capabilities for data visualization, reporting, planning, and predictive analytics. It is particularly well-suited for businesses that use SAP systems and are looking to gain insight into their data in a single, integrated platform.

Incentivized