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19 March 2023

Hive Vs RDBMS | Comparison | Difference

One of the most significant differences between the two systems is that the relational database management system(RDBMS) works on a relational database while a data warehouse software system called hive, offers data analysis and querying. You can check out the detailed information on Hive Vs RDBMS below. 

What is Hive?

A data warehouse software system called Hive offers data analysis and querying. Hive provides a querying interface similar to SQL for data stored in various Hadoop-integrated databases and file systems. Hive makes managing and querying large datasets very quick. It is a Hadoop ecosystem ETL tool.

What is RDBMS?

A relational database management system is a type of DBMS that is more sophisticated (RDBMS). In the 1970s, it first became visible. Organizations can access data more efficiently using RDBMS systems than they can with DBMS systems. A piece of software known as an RDBMS only stores information that must be kept in tables. Data is arranged and kept in this type of system in rows and columns known as tuples and attributes. RDBMS is a potent data management system that is used extensively all over the world

Hive Vs RDBMS  | Difference between Hive and RDBMS

  • Hive is used to maintain the data warehouse, While RDBMS is used to maintain the database.
  • Hive uses HQL(Hive Query Language), While RDBMS uses SQL(Structured Query Language).
  • Hive is schema Varies in it, Schema is fixed in RDBMS.
  • The table in the hive is dense, While tables in RDBMS are sparse. 
  • Normalized and de-normalized both types of data are stored in Hive, While Normalized data is stored in RDBMS.
  • Hive is based on the idea of writing once and reading many times. While RDBMS is built for reading and writing many times.
  • The maximum size allowed in Hive can be 100's petabytes very easily. While in RDBMS maximum data size allowed will be in tens of terabytes.
  • Hive is very easily scalable at a low cost, while RDBMS is not as easily scalable and is also very expensive to scale up.
  • Updates at the record level, insertions and delete transactions, and indexes are all possible with RDBMS, While Hive was designed to operate over HDFS data using MapReduce, where full table scans are the norm and a table update is accomplished by transforming the data into a new table. As a result, these are not permitted in Hive.
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