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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    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

    PrestoDB (or Presto)

    Score10 out of 10
    N/APresto is an open source SQL query engine designed to run queries on data stored in Hadoop or in traditional databases. Teradata supported development of Presto followed the acquisition of Hadapt and Revelytix.N/A
    Pricing
    Apache PigPrestoDB (or Presto)
    Editions & Modules
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    Offerings
    Pricing Offerings
    Apache PigPrestoDB (or Presto)
    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 PigPrestoDB (or Presto)
    Considered Both Products
    Apache
    No answer on this topic
    Open Source
    Chose PrestoDB (or Presto)
    I think Presto is one of the best solutions out there today at the cutting edge for interactive query analysis. One of the challenges is presto is a niche tool for the interactive query use case and doesn't have the knobs and whistles as much as Spark. In the foreseeable future …
    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
    No answers on this topic
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    Best Alternatives
    Apache PigPrestoDB (or Presto)
    Small Businesses
    No answers on this topic
    Amazon RDS
    Score8.1 out of 10
    Medium-sized Companies
    Cloudera Manager (no longer available standalone)
    Score9.9 out of 10
    SingleStore
    Score8.2 out of 10
    Enterprises
    Hadoop
    Score7.5 out of 10
    SAP IQ
    Score5.4 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Apache PigPrestoDB (or Presto)
    Likelihood to Recommend
    8.2
    (9 ratings)
    7.8
    (2 ratings)
    Usability
    10.0
    (1 ratings)
    -
    (0 ratings)
    Support Rating
    6.0
    (1 ratings)
    -
    (0 ratings)
    User Testimonials
    Apache PigPrestoDB (or Presto)
    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.
    Incentivized
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    Open Source
    Presto is for interactive simple queries, where Hive is for reliable processing. If you have a fact-dim join, presto is great..however for fact-fact joins presto is not the solution.. Presto is a great replacement for proprietary technology like Vertica
    Incentivized
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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.
    Incentivized
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    Open Source
    • Linking, embedding links and adding images is easy enough.
    • Once you have become familiar with the interface, Presto becomes very quick & easy to use (but, you have to practice & repeat to know what you are doing - it is not as intuitive as one would hope).
    • Organizing & design is fairly simple with click & drag parameters.
    Incentivized
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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.
    Incentivized
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    Open Source
    • Presto was not designed for large fact fact joins. This is by design as presto does not leverage disk and used memory for processing which in turn makes it fast.. However, this is a tradeoff..in an ideal world, people would like to use one system for all their use cases, and presto should get exhaustive by solving this problem.
    • Resource allocation is not similar to YARN and presto has a priority queue based query resource allocation..so a query that takes long takes longer...this might be alleviated by giving some more control back to the user to define priority/override.
    • UDF Support is not available in presto. You will have to write your own functions..while this is good for performance, it comes at a huge overhead of building exclusively for presto and not being interoperable with other systems like Hive, SparkSQL etc.
    Incentivized
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    Usability
    Apache
    It is quick, fast and easy to implement Apache Pig which makes is quite popular to be used.
    Incentivized
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    Open Source
    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.
    Incentivized
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    Open Source
    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.
    Incentivized
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    Open Source
    Presto is good for a templated design appeal. You cannot be too creative via this interface - but, the layout and options make the finalized visual product appealing to customers. The other design products I use are for different purposes and not really comparable to Presto.
    Incentivized
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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.
    Incentivized
    Read full review
    Open Source
    • Presto has helped scale Uber's interactive data needs. We have migrated a lot out of proprietary tech like Vertica.
    • Presto has helped build data driven applications on its stack than maintain a separate online/offline stack.
    • Presto has helped us build data exploration tools by leveraging it's power of interactive and is immensely valuable for data scientists.
    Incentivized
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