Apache Sqoop vs. VMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

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
VMware Tanzu Data Services
Score 8.4 out of 10
N/A
VMware Tanzu Data Services is a portfolio of on-demand caching, messaging, and database software on VMware Tanzu for development teams building modern applications.N/A
Pricing
Apache SqoopVMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache SqoopVMware Tanzu Data Services
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 SqoopVMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Top Pros
Top Cons
Best Alternatives
Apache SqoopVMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Small Businesses

No answers on this topic

Google BigQuery
Google BigQuery
Score 8.6 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.7 out of 10
Snowflake
Snowflake
Score 9.1 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 9.3 out of 10
Oracle Exadata
Oracle Exadata
Score 8.5 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache SqoopVMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
Likelihood to Recommend
9.0
(1 ratings)
8.0
(1 ratings)
Support Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Apache SqoopVMware Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)
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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VMware
If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.
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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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VMware
  • Apache MADlib provides popular machine learning functionality.
  • Allows you to query terabytes of data databases.
  • Interoperability for AWS S3 is effortless.
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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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VMware
  • Running on Azure is a little more difficult.
  • Synchronization with Kafka may be a little easier.
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Support Rating
Apache
No answers on this topic
VMware
They were very helpful. We needed support for initial implementation.
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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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VMware
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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VMware
  • There was a noticeable reduction in system reliability.
  • Saw a reduction in unsuccessful analytics operations.
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ScreenShots