What users are saying about
112 Ratings
2 Ratings
112 Ratings
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Score 8.3 out of 101
2 Ratings
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Score 8 out of 101

Likelihood to Recommend

Apache Spark

The software appears to run more efficiently than other big data tools, such as Hadoop. Given that, Apache Spark is well-suited for querying and trying to make sense of very, very large data sets. The software offers many advanced machine learning and econometrics tools, although these tools are used only partially because very large data sets require too much time when the data sets get too large. The software is not well-suited for projects that are not big data in size. The graphics and analytical output are subpar compared to other tools.
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SAP Vora

I spent more than 1 year with SAP Vora, SAP Datahub and SAP Leonardo with ML, iOt. I believe this product has potential but it is not easy to adopt. SAP has to keep in mind how open-source big data technologies are able to deliver quick results. I know SAP is stabilizing and fighting hard against many open source technologies, but it still has a long way to go there.
Dhinesh Kumar Ganeshan,PMP,CSM profile photo

Pros

Apache Spark

  • 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
Nitin Pasumarthy profile photo

SAP Vora

  • Can fetch the data from different sources like Big data, as well as on regular DBs, and generate the report in efficient way
  • With the SQL editor as its main component, developers can easily query with the request to meet the requirement with no extra effort
  • In-memory functionality is the biggest strength, as it provides output in a fast and quick manner.
Pradeep Bele profile photo

Cons

Apache Spark

  • 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
Anson Abraham profile photo

SAP Vora

  • Vora 2.0 in on premise scenarios could be improved, as adoption of the cloud is not an easy sell.
  • Kubernetes and Docker integration need to be more seamless and quick to understand. If this is simplified, it will be easy to adopt
  • Data hub orchestration and integrations could be simplified so that quick adoption within SAP BW, ECC, S4 HANa scenarios is possible.
Dhinesh Kumar Ganeshan,PMP,CSM profile photo

Alternatives Considered

Apache Spark

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.
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SAP Vora

We selected SAP VORA because we needed acclerated integration with different sources with a huge amount of data. Also the data de-duplication has easily eliminated the different entries in a fastest and enhanced way, which ultimately leads us and the customer to prefer SAP Vora against different products, and has helped eliminate any limitations in using and playing with our data lake.
Pradeep Bele profile photo

Return on Investment

Apache Spark

  • It has had a very positive impact, as it helps reduce the data processing time and thus helps us achieve our goals much faster.
  • Being easy to use, it allows us to adapt to the tool much faster than with others, which in turn allows us to access various data sources such as Hadoop, Apache Mesos, Kubernetes, independently or in the cloud. This makes it very useful.
  • It was very easy for me to use Apache Spark and learn it since I come from a background of Java and SQL, and it shares those basic principles and uses a very similar logic.
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SAP Vora

  • Negative impact would be Poc and RFI will need more time to adopt and decision making gets delayed
  • Positive impact would be it's a great leap from SAP to adopt a Big data technologies and AI within cloud stream. But selling is going to take time.
Dhinesh Kumar Ganeshan,PMP,CSM profile photo

Pricing Details

Apache Spark

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

SAP Vora

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

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