Difference between Pig and Hive Last Updated : 23 Jun, 2022 Comments Improve Suggest changes Like Article Like Report 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 : S.No.PigHive1.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.17.It is very easy to write UDFs to calculate matrices.It does support UDFs but is much hard to debug. Comment More infoAdvertise with us Next Article Difference between Pig and Hive bansal_rtk_ Follow Improve Article Tags : DBMS Difference Between Apache Pig Similar Reads Difference between Hue and Pig 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 2 min read Difference Between Hive and Hue To process and analyze big data, organizations use Hadoop, an open-source framework that handles vast amounts of structured and unstructured data. Within the Hadoop ecosystem, Hive and Hue serve different purposes. Hive is a data warehouse tool that enables users to run SQL-like queries on large dat 5 min read Difference between Hive and MongoDB 1. Hive : Hive is a data warehouse software for querying and managing large distributed datasets, built on Hadoop. It is developed by Apache Software Foundation in 2012. It contains two modules, one is MapReduce and another is Hadoop Distributed File System (HDFS). It stores schema in a database and 2 min read Difference between SQL and HiveQL 1. Structured Query Language (SQL): SQL is a domain-specific language used in programming and designed for managing data held in a relational database management system also known as RDBMS. It is also useful in handling structured data, i.e., data incorporating relations among entities and variables 2 min read Difference between RDBMS and Hive RDBMS and Hivey are both strong tools for organizing and accessing data, Relational Database Management Systems (RDBMS) and Apache Hive are designed for distinct use cases and goals. Hive is intended to manage large-scale data analytics and querying on top of the Hadoop environment, while RDBMS is g 4 min read Difference between Hive and Oracle 1. Hive : Hive is an open-source data warehouse software. It is built on the top of Hadoop. It also provides HiveQL which is similar to SQL. Hive is used for querying and managing distributed datasets built on Hadoop. Hive uses RDBMS as a primary database model. 2. Oracle : Oracle is commercial soft 2 min read Difference between MapReduce and Pig MapReduce is a model that works over Hadoop to access big data efficiently stored in HDFS (Hadoop Distributed File System). It is the core component of Hadoop, which divides the big data into small chunks and process them parallelly. Features of MapReduce: It can store and distribute huge data acros 2 min read Difference between Hive and HBase Hive and HBase are both Apache Hadoop-based technologies, but they have different use cases and characteristics: Data Model: Hive uses a SQL-like language called HiveQL to process structured data stored in Hadoop Distributed File System (HDFS). HBase, on the other hand, is a NoSQL database that stor 4 min read Difference between Hive and Derby 1. Hive : Hive is a data warehouse software for querying and managing large distributed datasets, built on Hadoop. It is developed by Apache Software Foundation in 2012. It contains two modules, one is MapReduce and another is Hadoop Distributed File System (HDFS). It stores schema in a database and 2 min read Difference Between EMR and Glue Pre-requisite:- AWS Amazon Web Services (AWS), a subsidiary of Amazon.com, has invested billions of dollars in IT resources distributed across the globe. These resources are shared among all the AWS account holders across the globe. These accounts themselves are entirely isolated from each other. AW 3 min read Like