Apache Drill vs. SAP Vora

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Drill
Score 8.1 out of 10
N/A
Apache Drill is a schema-free query engine for use with NoSQL or Hadoop data or file storage systems and databases.N/A
SAP Vora
Score 6.0 out of 10
N/A
SAP Vora is a computing engine designed to provide better accessibility to Hadoop data from SAP HANA. SAP Vora manages unstructured Hadoop data by building structured data hierarchies and making the data queryable through an SQL interface.N/A
Pricing
Apache DrillSAP Vora
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache DrillSAP Vora
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Apache DrillSAP Vora
Top Pros
Top Cons
Best Alternatives
Apache DrillSAP Vora
Small Businesses
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10

No answers on this topic

Medium-sized Companies
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM Cloudant
IBM Cloudant
Score 8.4 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 8.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache DrillSAP Vora
Likelihood to Recommend
8.0
(1 ratings)
6.0
(1 ratings)
Likelihood to Renew
7.0
(1 ratings)
-
(0 ratings)
User Testimonials
Apache DrillSAP Vora
Likelihood to Recommend
Apache
if you're doing joins from hBASE, hdfs, cassandra and redis, then this works. Using it as a be all end all does not suit it. This is not your straight forward magic software that works for all scenarios. One needs to determine the use case to see if Apache Drill fits the needs. 3/4 of the time, usually it does.
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SAP
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.
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Pros
Apache
  • queries multiple data sources with ease.
  • supports sql, so non technical users who know sql, can run query sets
  • 3rd party tools, like tableau, zoom data and looker were able to connect with no issues
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SAP
  • 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
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Cons
Apache
  • deployment. Not as easy
  • configuration isn't as straight forward, especially with the documentation
  • Garbage collection could be improved upon
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SAP
  • 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.
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Likelihood to Renew
Apache
if Presto comes up with more support (ie hbase, s3), then its strongly possible that we'll move from apache drill to prestoDB. However, Apache drill needs more configuration ease, especially when it comes to garbage collection tuning. If apache drill could support also sparkSQL and Flume, then it does change drill into being something more valuable than prestoDB
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SAP
No answers on this topic
Alternatives Considered
Apache
compared to presto, has more support than prestodb. Impala has limitations to what drill can support apache phoenix only supports for hbase. no support for cassandra. Apache drill was chosen, because of the multiple data stores that it supports htat the other 3 do not support. Presto does not support hbase as of yet. Impala does not support query to cassandra
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SAP
No answers on this topic
Return on Investment
Apache
  • Configuration has taken some serious time out.
  • Garbage collection tuning. is a constant hassle. time and effort applied to it, vs dedicating resources elsewhere.
  • w/ sql support, reduces the need of devs to generate the resultset for analysts, when they can run queries themselves (if they know sql).
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SAP
  • 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.
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ScreenShots