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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 Pig

    Score8.4 out of 10
    N/AApache Pig is an open-source platform for processing and analyzing large datasets in distributed environments. It provides Pig Latin, a high-level dataflow language for defining transformations, and an execution layer that converts those programs into parallel processing jobs.

    $0

    Pricing
    HadoopApache Pig
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    HadoopApache Pig
    Free Trial
    NoNo
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeNo setup fee
    Additional Details——
    More Pricing Information
    Community Pulse
    HadoopApache Pig
    Considered Both Products
    Apache
    Chose Hadoop
    • For real-time streaming, use Spark; can provide a stark contrast to the way MR works
    • Hadoop offers a scalable, cost-effective and highly available solution for big data storage and processing.
    • Amazon Redshift is somewhat closer to Hadoop. But to analyze Petabytes of data Hadoop …
    Incentivized
    Chose Hadoop
    Hadoop provides storage for large data sets and a powerful processing model to crunch and transform huge amounts of data. It does not assume the underlying hardware or infrastructure and enables the users to build data processing infrastructure from commodity hardware. All the …
    Incentivized
    Apache
    Chose Apache Pig
    - Provided better ways for optimized hadoop jobs than Hive but not anymore.
    - Spark DSL is much more advanced and compute times are significantly less.
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    7 Answers
    80%
    Would buy again
    4 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    7 Answers
    100%
    Delivers good value for the price
    5 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    7 Answers
    80%
    Happy with the feature set
    4 Answers
    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 Pig
    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
    Cloudera Manager (no longer available standalone)
    Score9.9 out of 10
    Enterprises
    Amazon EMR
    Score9.1 out of 10
    Hadoop
    Score7.5 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    HadoopApache Pig
    Likelihood to Recommend
    8.0
    (37 ratings)
    8.2
    (9 ratings)
    Likelihood to Renew
    9.6
    (8 ratings)
    -
    (0 ratings)
    Usability
    8.0
    (6 ratings)
    10.0
    (1 ratings)
    Performance
    8.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    7.5
    (3 ratings)
    6.0
    (1 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 Pig
    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
    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.
    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.
    Incentivized
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    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.
    Incentivized
    Read full review
    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
    Incentivized
    Read full review
    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.
    Incentivized
    Read full review
    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
    Read full review
    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.
    Incentivized
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    Apache
    It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
    Incentivized
    Read full review
    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.
    Incentivized
    Read full review
    Apache
    The documentation is adequate. I'm not sure how large of an external community there is for support.
    Incentivized
    Read full review
    Online Training
    Apache
    Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
    Read full review
    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.
    Incentivized
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    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.
    Incentivized
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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.
    Incentivized
    Read full review
    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.
    Incentivized
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