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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Apache Pig

    Score8.4 out of 10
    N/AApache Pig is a programming tool for creating MapReduce programs used in Hadoop.

    $0

    Apache Sqoop

    Score8.8 out of 10
    N/AApache Sqoop is a tool for use with Hadoop, used to transfer data between Apache Hadoop and other, structured data stores.N/A
    Pricing
    Apache PigApache Sqoop
    Editions & Modules
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    Offerings
    Pricing Offerings
    Apache PigApache Sqoop
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    Apache PigApache Sqoop
    Considered Both Products
    Apache
    No answer on this topic
    Apache
    Chose Apache Sqoop
    • 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 …
    Incentivized
    Key User Insights
    Would buy again
    80%
    Would buy again
    4 Answers
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    Delivers good value for the price
    100%
    Delivers good value for the price
    5 Answers
    No answers on this topic
    Happy with the feature set
    80%
    Happy with the feature set
    4 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    No answers on this topic
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    Implementation went as expected
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    Best Alternatives
    Apache PigApache Sqoop
    Small Businesses
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    Medium-sized Companies
    Cloudera Manager
    Score9.9 out of 10
    Cloudera Manager
    Score9.9 out of 10
    Enterprises
    Apache Spark
    Score9.2 out of 10
    Apache Spark
    Score9.2 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Apache PigApache Sqoop
    Likelihood to Recommend
    8.2
    (9 ratings)
    9.0
    (1 ratings)
    Usability
    10.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    6.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Apache PigApache Sqoop
    Likelihood to Recommend
    Apache
    Apache Pig is best suited for ETL-based data processes. It is good in performance in handling and analyzing a large amount of data. it gives faster results than any other similar tool. It is easy to implement and any user with some initial training or some prior SQL knowledge can work on it. Apache Pig is proud to have a large community base globally.
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    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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    Pros
    Apache
    • Its performance, ease of use, and simplicity in learning and deployment.
    • Using this tool, we can quickly analyze large amounts of data.
    • It's adequate for map-reducing large datasets and fully abstracted MapReduce.
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    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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    Cons
    Apache
    • UDFS Python errors are not interpretable. Developer struggles for a very very long time if he/she gets these errors.
    • Being in early stage, it still has a small community for help in related matters.
    • It needs a lot of improvements yet. Only recently they added datetime module for time series, which is a very basic requirement.
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    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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    Usability
    Apache
    It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
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    Apache
    No answers on this topic
    Support Rating
    Apache
    The documentation is adequate. I'm not sure how large of an external community there is for support.
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    Apache
    No answers on this topic
    Alternatives Considered
    Apache
    Apache Pig might help to start things faster at first and it was one of the best tool years back but it lacks important features that are needed in the data engineering world right now. Pig also has a steeper learning curve since it uses a proprietary language compared to Spark which can be coded with Python, Java.
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    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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    Return on Investment
    Apache
    • Higher learning curve than other similar technologies so on-boarding new engineers or change ownership of Apache Pig code tends to be a bit of a headache
    • Once the language is learned and understood it can be relatively straightforward to write simple Pig scripts so development can go relatively quickly with a skilled team
    • As distributed technologies grow and improve, overall Apache Pig feels left in the dust and is more legacy code to support than something to actively develop with.
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    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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