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CDAP vs Pig

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CDAP
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108
+ 1
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Pig
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CDAP vs Pig: What are the differences?

What is CDAP? Open source virtualization platform for Hadoop data and apps. Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements.

What is Pig? Platform for analyzing large data sets. Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce. .

CDAP and Pig belong to "Big Data Tools" category of the tech stack.

CDAP and Pig are both open source tools. It seems that Pig with 583 GitHub stars and 449 forks on GitHub has more adoption than CDAP with 346 GitHub stars and 178 GitHub forks.

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Pros of CDAP
Pros of Pig
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    • 2
      Finer-grained control on parallelization
    • 1
      Proven at Petabyte scale
    • 1
      Open-source
    • 1
      Join optimizations for highly skewed data

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    - No public GitHub repository available -

    What is CDAP?

    Cask Data Application Platform (CDAP) is an open source application development platform for the Hadoop ecosystem that provides developers with data and application virtualization to accelerate application development, address a broader range of real-time and batch use cases, and deploy applications into production while satisfying enterprise requirements.

    What is Pig?

    Pig is a dataflow programming environment for processing very large files. Pig's language is called Pig Latin. A Pig Latin program consists of a directed acyclic graph where each node represents an operation that transforms data. Operations are of two flavors: (1) relational-algebra style operations such as join, filter, project; (2) functional-programming style operators such as map, reduce.

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    Jobs that mention CDAP and Pig as a desired skillset
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    What companies use CDAP?
    What companies use Pig?
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    What tools integrate with CDAP?
    What tools integrate with Pig?
    What are some alternatives to CDAP and Pig?
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Akutan
    A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.
    Apache NiFi
    An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.
    StreamSets
    An end-to-end data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps.
    See all alternatives

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