In RDMS like MySQL thereis database, are there database also on the Hive ?as i read on the manual, hive only have table, i bit confuse about it..
and what is different concept of RDBMS and Hive ?
Tks before
Key differences between Hive and SQL: Architecture: Hive is a data warehouse project for data analysis; SQL is a programming language. (However, Hive performs data analysis via a programming language called HiveQL, similar to SQL.) Set-up: Hive is a data warehouse built on the open-source software program Hadoop.
It can be structured, semi-structured, and unstructured. Both RDBMS and Hadoop works on storing the data. RDBMS usually stores structured data whereas Hadoop stores unstructured, semi-structured, and even structured data. In this tutorial we will discuss the main differences between RDBMS and Hadoop.
No, we cannot call Apache Hive a relational database, as it is a data warehouse which is built on top of Apache Hadoop for providing data summarization, query and, analysis. It differs from a relational database in a way that it stores schema in a database and processed data into HDFS.
The main difference between RDBMs databases and Hive is specialization. While MySQL is general purpose database suited both for transactional processing (OLTP) and for analytics (OLAP), Hive is built for the analytics only. Technically the main difference is lack of update/delete
functioality. Data can only by be added and selected. In the same time Hive is capable of processing data volumes which can not be processed by MySQL or other conventional RDBMS (in shy budget).
MPP (massive parallel proecssing) databases are closest to the Hive by their functionality - while they have full SQL support they are scalable up to hundreds of computers.
Another serious different - is query language.
Hive do not support full SQL even in select because of it's implementation. In my view main difference is lack of join for any condition other then equal.
Hive query language sintax is also a bit different so you can not connect report generation software right to Hive.
Basically, hive is a sql-like scripting language built on MapReduce. When you issue commands, the commands are interpreted and ran over the distributed system. Since the files being crunched are flat, it is equivalent to running an equivalent code in Hadoop, and gathering the data. The whole flow is much slower than it would be if you used Mysql.
Hive vs Traditional database Hive --> Schema on READ - it's does not verify the schema while it's loaded the data Traditional database ---> Schema on WRITE - table schema is enforced at data load time i.e if the data being loaded does't conformed on schema in that case it will rejected
Hive -->It's very easily scalable at low cost
Traditional database ---> Not much Scalable, costly scale up.
Hive -->It's based on hadoop notation that is Write once and read many times
Traditional database ---> In traditional database we can read and write many time
Hive -->Record level updates is not possible in Hive
Traditional database ---> Record level updates, insertions and
deletes, transactions and indexes are possible
Hive -->OLTP (On-line Transaction Processing) is not yet supported in Hive but it's supported OLAP (On-line Analytical Processing) Traditional database --->Both OLTP (On-line Transaction Processing) and OLAP (On-line Analytical Processing) are supported in RDBMS.
or else please check the below URL
https://sensaran.wordpress.com/2016/01/30/comparison-with-hive-with-traditional-database/
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