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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Hadoop

    Score7.5 out of 10
    N/AHadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A

    Apache Sqoop (discontinued)

    Score8.8 out of 10
    N/AApache Sqoop is a discontinued open-source command-line tool for bulk data transfer between Apache Hadoop and structured data stores. It was commonly used to import relational database tables or mainframe datasets into HDFS for processing with Hadoop tools, then export processed data back to a relational database.N/A
    Pricing
    HadoopApache Sqoop (discontinued)
    Editions & Modules
    No answers on this topic
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    Offerings
    Pricing Offerings
    HadoopApache Sqoop (discontinued)
    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
    HadoopApache Sqoop (discontinued)
    Considered Both Products
    Apache
    No answer on this topic
    Apache
    Chose Apache Sqoop (discontinued)
    • 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
    100%
    Would buy again
    7 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    7 Answers
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    7 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    6 Answers
    No answers on this topic
    Implementation went as expected
    80%
    Implementation went as expected
    4 Answers
    No answers on this topic
    Best Alternatives
    HadoopApache Sqoop (discontinued)
    Small Businesses
    No answers on this topic
    No answers on this topic
    Medium-sized Companies
    Cloudera Manager (no longer available standalone)
    Score9.9 out of 10
    Apache Spark
    Score8.8 out of 10
    Enterprises
    Amazon EMR
    Score9.1 out of 10
    Apache Spark
    Score8.8 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HadoopApache Sqoop (discontinued)
    Likelihood to Recommend
    8.0
    (37 ratings)
    9.0
    (1 ratings)
    Likelihood to Renew
    9.6
    (8 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (6 ratings)
    -
    (0 ratings)
    Performance
    8.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    7.5
    (3 ratings)
    -
    (0 ratings)
    Online Training
    6.1
    (2 ratings)
    -
    (0 ratings)
    Data Sharing and Collaboration
    7.7
    (10 ratings)
    -
    (0 ratings)
    Data Sources
    8.7
    (10 ratings)
    -
    (0 ratings)
    User Testimonials
    HadoopApache Sqoop (discontinued)
    Likelihood to Recommend
    Apache
    Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
    Incentivized
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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
    Incentivized
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    Pros
    Apache
    • Handles large amounts of unstructured data well, for business level purposes
    • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
    • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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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
    • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
    • Not for small data sets
    • Data security needs to be ramped up
    • Failure in NameNode has no replication which takes a lot of time to recover
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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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    Likelihood to Renew
    Apache
    Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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    Apache
    No answers on this topic
    Usability
    Apache
    As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
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    Apache
    No answers on this topic
    Support Rating
    Apache
    It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
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    Apache
    No answers on this topic
    Online Training
    Apache
    Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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    Apache
    No answers on this topic
    Alternatives Considered
    Apache
    Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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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
    • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
    • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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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.
    Incentivized
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