Hadoop vs NoSQL

As big data continues down its path of growth, there is no doubt that these innovative approaches, utilizing NoSQL database architecture and Hadoop software that will be central to allowing companies reach full potential with data. Although we know that they are particularly different to one and each other, we can know deeply what things that make them difference and what kind of factors contain in each software with the sophisticated technology in managing the data for our computers. Here we show you the article of Hadoop vs NoSQL.

Hadoop was originally developed by Doug Cutting and Mike Cafarella in 2005 who was then working at Yahoo. The name Hadoop based on toys ‘ Elephant ‘ child of Doug Cutting. Hadoop is a framework or platform Java-based open source under the Apache license for a support application on Big Data and connecting several computers so that they can cooperate and sync in storing and processing data. Google’s MapReduce technology using Hadoop and Google File System (GFS) as its foundation. The system of Hadoop can divide the process of calculation or computation that usually takes a very long time or almost not possible by a single computer. The system can divide the burden of storage to different computers so that if one or more of the dead computer, the data will still be awake. This system is referred to as the Hadoop Distributed File System (HDFS). Hadoop framework is composed of several parts are Common, Hadoop Hadoop Distributed File System, Hadoop YARN, and Hadoop MapReduce.

NoSQL is a concept of non-relational data storage. Unlike the relational database model which during use, NoSQL use some different methods. This method depends on the type of database being used. Since the concept itself is a NoSQL database, and on its implementation, many types of NoSQL. In NoSQL, there are a variety of forms of database with the schema and concept of its own. Same is the case with SQL databases like friends know like MySQL, SQL Server, Oracle, PostgreSQL, and others. In MongoDB, NoSQL, there are ripples of CouchDB, and others. ANE will discuss some of the NoSQL databases. NoSQL is very useful in data-data that is constantly evolving, where data is so complex that a relational database can no longer accommodate. One of its forms is an interrelated data to one another, then it would appear the process of duplication of data. Where data of mutual calling to some new data, an additional request, data changes, and others with the same key. (Read also : NoSQL vs MySQL)

- Not type of a database- Commonly referred to as Not Only SQL
- A staple of the Hadoop ecosystem is MapReduce- Well-adapted database infrastructure to the heavy demands of big data
- An enabler of certain types NoSQL distributed databases- Highly structured

Currently, we have the difference between Hadoop and NoSQL. Hadoop refers to an ecosystem of software packages, including MapReduce, HDFS, and a whole host of other software packages to support the import and export of data into and from HDFS. While NoSQL refers to non-relational or at least non-SQL database solutions such as HBase (also a part of the Hadoop ecosystem), Cassandra, MongoDB, Riak, CouchDB, and many others. In short, we can say that they are not the same thing, but are related to data intend.

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