Apache Sqoop vs. SAP Vora

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Sqoop
Score 8.8 out of 10
N/A
Apache Sqoop is a tool for use with Hadoop, used to transfer data between Apache Hadoop and other, structured data stores.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 SqoopSAP Vora
Editions & Modules
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Offerings
Pricing Offerings
Apache SqoopSAP 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 SqoopSAP Vora
Top Pros
Top Cons
Best Alternatives
Apache SqoopSAP Vora
Small Businesses

No answers on this topic

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Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 9.1 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 9.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SqoopSAP Vora
Likelihood to Recommend
9.0
(1 ratings)
6.0
(1 ratings)
User Testimonials
Apache SqoopSAP Vora
Likelihood to Recommend
Apache
Sqoop is great for sending data between a JDBC compliant database and a Hadoop environment. Sqoop is built for those who need a few simple CLI options to import a selection of database tables into Hadoop, do large dataset analysis that could not commonly be done with that database system due to resource constraints, then export the results back into that database (or another). Sqoop falls short when there needs to be some extra, customized processing between database extract, and Hadoop loading, in which case Apache Spark's JDBC utilities might be preferred
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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
  • Provides generalized JDBC extensions to migrate data between most database systems
  • Generates Java classes upon reading database records for use in other code utilizing Hadoop's client libraries
  • Allows for both import and export features
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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
  • Sqoop2 development seems to have stalled. I have set it up outside of a Cloudera CDH installation, and I actually prefer it's "Sqoop Server" model better than just the CLI client version that is Sqoop1. This works especially well in a microservices environment, where there would be only one place to maintain the JDBC drivers to use for Sqoop.
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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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Alternatives Considered
Apache
  • Sqoop comes preinstalled on the major Hadoop vendor distributions as the recommended product to import data from relational databases. The ability to extend it with additional JDBC drivers makes it very flexible for the environment it is installed within.
  • Spark also has a useful JDBC reader, and can manipulate data in more ways than Sqoop, and also upload to many other systems than just Hadoop.
  • Kafka Connect JDBC is more for streaming database updates using tools such as Oracle GoldenGate or Debezium.
  • Streamsets and Apache NiFi both provide a more "flow based programming" approach to graphically laying out connectors between various systems, including JDBC and Hadoop.
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SAP
No answers on this topic
Return on Investment
Apache
  • When combined with Cloudera's HUE, it can enable non-technical users to easily import relational data into Hadoop.
  • Being able to manipulate large datasets in Hadoop, and them load them into a type of "materialized view" in an external database system has yielded great insights into the Hadoop datalake without continuously running large batch jobs.
  • Sqoop isn't very user-friendly for those uncomfortable with a CLI.
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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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