What is the difference between Pig and Sqoop in Hadoop ?

Answer:Apache Pig is a tool for analytics which is used to analyze data stored in HDFS. Apache Sqoop is a tool to importing structured data from RDBMS to HDFS or exporting data from HDFS to RDBMS.

Difference between Pig and Sqoop in Hadoop

Pig Sqoop
Apache Pig is a tool for analytics which is used to
analyze data stored in HDFS.
Apache Sqoop is a tool to importing structured data from RDBMS to HDFS or exporting data from HDFS to RDBMS.
We can import the data from Sql databases into
hive rather than NoSql Databases.
It can integrate with any external data sources with HDFS i.e Sql , NoSql and Data warehouses as well using this tool at the same time we export it as well since this can be used as bi-directional ways
Pig can be used for following purposes ETL
data pipeline, Research on raw data.
Important Sqoop control commands to import RDBMS data are Append, Columns and Where
The pig Metastore stores all info about the tables.
And we can execute spark sql queries because spark
can interact with pig Metastore.
Sqoop metastore is a tool for using hosts in a shared metadata repository. Multiple users and remote users can define and execute saved jobs defined in metastore.
The scalar data types in pig are int, float,
double, long, chararray, and bytearray. The complex data
types in Pig are map, tuple, and bag.
It basically converts CHAR(x), VARCHAR(x), NUMERIC(x,y) to string (with lengh 32767), and it converts DATETIME to BIGINT.
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