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 680 GitHub stars and 450 GitHub forks. Here’s a link to Pig's open source repository on GitHub
Who uses Pig?
Companies
14 companies reportedly use Pig in their tech stacks, including Netflix, GittiGidiyor, and Platform.
Developers
45 developers on StackShare have stated that they use Pig.
Pig Integrations
Pros of Pig
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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.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system
that supports an extended subset of the SQL standard, including
transactions, foreign keys, subqueries, triggers, user-defined types
and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
