Apache Spark vs. Pig vs. Airpal

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Heads up: you're comparing apples to oranges. Tools belonging to different groups are often not directly comparable because they usually have different intended purposes and benefits.

Apache Spark

Pig

Airpal

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Description

What is 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.

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.

What is Airpal?

A web-based query execution tool built on top of Facebook's PrestoDB.

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Why do you like Apache Spark?

Pros
Why do you like Pig?

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Why do you like Airpal?

Companies

221 Companies Using Apache Spark
7 Companies Using Pig
2 Companies Using Airpal

Integrations

Apache Spark Integrations
Pig Integrations
Airpal Integrations

What are some alternatives to Apache Spark, Pig, and Airpal?

  • Apache Flink - Fast and reliable large-scale data processing engine
  • Druid - Fast column-oriented distributed data store
  • Presto - Distributed SQL Query Engine for Big Data (by Facebook)
  • Amazon Athena - Query S3 Using SQL

See all alternatives to Apache Spark



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