What users are saying about
18 Ratings
2 Ratings
18 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 7.3 out of 101
2 Ratings
<a href='https://www.trustradius.com/static/about-trustradius-scoring' target='_blank' rel='nofollow'>trScore algorithm: Learn more.</a>
Score 8 out of 101

Add comparison

Likelihood to Recommend

Apache Pig

Apache Pig is well suited as part of an ongoing data pipeline where there is already a team of engineers in place that are familiar with the technology since at this point I would consider it relatively depreciated since there are more suitable technologies that have more robust and flexible APIs with the added benefit of being easier to learn and apply. For ad-hoc needs, I would recommend Hive or Spark-SQL if a SQL-esque language makes sense otherwise to make use of Spark + a Notebook technology such as Apache Zeppelin. For production data pipelines I would recommend Apache Spark over Apache Pig for its performance, ease of use, and its libraries.
No photo available

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 pig DSL provides a better alternative to Java map reduce code and the instruction set is very easy to learn and master.
  • It has many advanced features built-in such as joins, secondary sort, many optimizations, predicate push-down, etc.
  • When Hive was not very advanced (extremely slow) few years ago, pig has always been the go to solution. Now with Spark and Hive (after significant updates), the need to learn apache pig may be questionable.
No photo available
  • Modelling with SAP HANA and Hadoop
  • Realtime Analysis using Vora and HANA as a Streaming engine
  • Time series Analysis on large chunks of datasets
  • Machine learning capabilities on Hadoop tables and spark contexts
Dhinesh Kumar Ganeshan,PMP,CSM profile photo

Cons

  • Improve Spark support and compatibility
  • Spark and Hive are already being used main-stream, both of them have an instruction set that is easier to learn and master in a matter of days. While apache pig used to be a great alternative to writing java map reduce, Hive after significant updates is now either equal or better than pig.
No photo available
  • 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

Usability

Apache Pig10.0
Based on 1 answer
It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
Subhadipto Poddar profile photo
No score
No answers yet
No answers on this topic

Alternatives Considered

- Provided better ways for optimized hadoop jobs than Hive but not anymore.- Spark DSL is much more advanced and compute times are significantly less.
No photo available
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

  • The ROI was definitely positive in the beginning, but hard to say the same now due to advancements in Hive and Spark.
No photo available
  • 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 Pig

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

SAP Vora

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