{"id":154,"date":"2018-10-17T04:56:27","date_gmt":"2018-10-17T04:56:27","guid":{"rendered":"https:\/\/www.appservgrid.com\/paw92\/index.php\/2018\/10\/17\/orientdb-how-to-install-the-nosql-database-on-centos-7\/"},"modified":"2018-10-17T04:56:27","modified_gmt":"2018-10-17T04:56:27","slug":"orientdb-how-to-install-the-nosql-database-on-centos-7","status":"publish","type":"post","link":"https:\/\/www.appservgrid.com\/paw92\/index.php\/2018\/10\/17\/orientdb-how-to-install-the-nosql-database-on-centos-7\/","title":{"rendered":"OrientDB: How To Install the NoSQL DataBase on CentOS 7"},"content":{"rendered":"


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\n \"OrientDB<\/a> <\/p>\n

Introduction \u2013 NoSQL and OrientDB<\/h3>\n

When talking about databases, in general, we refer to two major families: RDBMS (Relational Database Management System), which use as user and application program interface a language named Structured Query Language (or SQL) and non-relational database management systems, or NoSQL databases. OrientDB is part of the second family.<\/p>\n

Between the two models there is a huge difference in the way they consider (and store) data.<\/p>\n

Relational Database Management Systems<\/h4>\n

In the relational model (like MySQL, or its fork, MariaDB), a database is a set of tables, each containing one or more data categories organized in columns. Each row of the DB contains a unique instance of data for categories defined by columns.<\/p>\n

Just as an example, consider a table containing customers. Each row correspond to a customer, with columns for name, address, and every required information.
\nAnother table could contain an order, with product, customer, date and everything else. A user of this DB can obtain a view that fits its needs, for example a report about customers that bought products in a specific range of prices.<\/p>\n

NoSQL Database Management Systems<\/h4>\n

In the NoSQL (or Not only SQL) database management systems, databases are designed implementing different \u201cformats\u201d for data, like a document, key-value, graph and others. The database systems realized with this paradigm are built especially for large-scale database clusters, and huge web applications. Today, NoSQL databases are used by major companies like Google and Amazon.<\/p>\n

Document databases<\/h5>\n

Document databases store data in document format. The usage of this kind of DBs is usually raised with JavaScript and JSON, however, XML and other formats are accepted. An example is MongoDB.<\/p>\n

Key-value databases<\/h5>\n

This is a simple model pairing a unique key with a value. These systems are performant and highly scalable for caching. Examples include BerkeleyDB and MemcacheDB.<\/p>\n

Graph databases<\/h5>\n

As the name predicts, these databases store data using graph models, meaning that data is organized as nodes and interconnections between them. This is a flexible model which can evolve over time and use. These systems are applied where there is the necessity of mapping relationships.
\nExamples are IBM Graphs and Neo4j and OrientDB.<\/p>\n

OrientDB<\/h3>\n

OrientDB, as stated by the company behind it, is a multi-model NoSQL Database Management System that \u201ccombines the power of graphs with documents, key\/value, reactive, object-oriented and geospatial models into one scalable, high-performance operational database\u201c.<\/em><\/p>\n

OrientDB has also support for SQL, with extensions to manipulate trees and graphs.<\/p>\n

Prerequisites<\/h3>\n