38
52
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4

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.
Pig is a tool in the Big Data Tools category of a tech stack.
Pig is an open source tool with 591 GitHub stars and 448 GitHub forks. Here’s a link to Pig's open source repository on GitHub

Who uses Pig?

Companies
12 companies reportedly use Pig in their tech stacks, including Netflix, Outbrain, and Cobrain.

Developers
26 developers on StackShare have stated that they use Pig.

Pig Integrations

Why developers like Pig?

Here’s a list of reasons why companies and developers use Pig

Pig Alternatives & Comparisons

What are some alternatives to Pig?
Capybara
Capybara helps you test web applications by simulating how a real user would interact with your app. It is agnostic about the driver running your tests and comes with Rack::Test and Selenium support built in. WebKit is supported through an external gem.
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.
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Apache Hive
Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
See all alternatives

Pig's Followers
52 developers follow Pig to keep up with related blogs and decisions.
harrisj09
visceralnair
Mehrdad Mehralian
Rajan Vyas
Yury Buldakov
John Alton
Sam Chaher
Daniel Seymour
Gabriel Georgescu
Krishnan Subramanian