1. Pig :
Pig is used for the analysis of a large amount of data. It is abstract over MapReduce. Pig is used to perform all kinds of data manipulation operations in Hadoop. It provides the Pig-Latin language to write the code that contains many inbuilt functions like join, filter, etc. The two parts of the Apache Pig are Pig-Latin and Pig-Engine. Pig Engine is used to convert all these scripts into a specific map and reduce tasks. Pig abstraction is at a higher level. It contains less line of code as compared to MapReduce.
2. Hive :
Hive is built on the top of Hadoop and is used to process structured data in Hadoop. Hive was developed by Facebook. It provides various types of querying language which is frequently known as Hive Query Language. Apache Hive is a data warehouse and which provides an SQL-like interface between the user and the Hadoop distributed file system (HDFS) which integrates Hadoop.
Difference between Pig and Hive :
|1.||Pig operates on the client side of a cluster.||Hive operates on the server side of a cluster.|
|2.||Pig uses pig-latin language.||Hive uses HiveQL language.|
|3.||Pig is a Procedural Data Flow Language.||Hive is a Declarative SQLish Language.|
|4.||It was developed by Yahoo.||It was developed by Facebook.|
|5.||It is used by Researchers and Programmers.||It is mainly used by Data Analysts.|
|6.||It is used to handle structured and semi-structured data.||It is mainly used to handle structured data.|
|7.||It is used for programming.||It is used for creating reports.|
|8.||Pig scripts end with .pig extension.||In HIve, all extensions are supported.|
|9.||It does not support partitioning.||It supports partitioning.|
|10.||It loads data quickly.||It loads data slowly.|
|11.||It does not support JDBC.||It supports JDBC.|
|12.||It does not support ODBC.||It supports ODBC.|
|13.||Pig does not have a dedicated metadata database.||Hive makes use of the exact variation of dedicated SQL-DDL language by defining tables beforehand.|
|14.||It supports Avro file format.||It does not support Avro file format.|
|15.||Pig is suitable for complex and nested data structures.||Hive is suitable for batch-processing OLAP systems.|
|16.||Pig does not support schema to store data.||Hive supports schema for data insertion in tables.|
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