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Apache Kudu vs Pig

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Apache Kudu
72
258
+ 1
10
Pig
59
111
+ 1
5
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Kudu vs Pig: What are the differences?

What is Kudu? Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform. A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

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. .

Kudu and Pig can be categorized as "Big Data" tools.

Kudu and Pig are both open source tools. Kudu with 789 GitHub stars and 263 forks on GitHub appears to be more popular than Pig with 583 GitHub stars and 449 GitHub forks.

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Pros of Apache Kudu
Pros of Pig
  • 10
    Realtime Analytics
  • 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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Cons of Apache Kudu
Cons of Pig
  • 1
    Restart time
    Be the first to leave a con

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    What is Apache Kudu?

    A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

    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 Apache Kudu and Pig as a desired skillset
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    What companies use Apache Kudu?
    What companies use Pig?
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    What tools integrate with Apache Kudu?
    What tools integrate with Pig?
    What are some alternatives to Apache Kudu and Pig?
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    HBase
    Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
    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.
    Apache Impala
    Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
    Hadoop
    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
    See all alternatives

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