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Relational Database vs. Non-Relational Database

More Posted time:Jun 24, 2016 21:36 PM
Relational Database vs. Non-Relational Database

A database management system is a software application that interacts with users, applications, and databases to capture and analyze data. Database management systems allow the definition, creation, querying, update, and administration of databases.

Database management systems have been broadly classified into two groups:
Relational databases also called relational database management systems or SQL databases. The most popular of these being Microsoft SQL Server, Oracle Database, MySQL and IBM DB2.
Non-relational databases also called NoSQL databases, the most popular ones being MongoDB, DocumentDB, Cassandra, Couchbase, HBase, Redis, and Neo4j.

For over two decades we have known how to handle relational data – simply put it in a relational database management system and use SQL to work on the data. Lately we have seen an increasing trend towards NoSQL databases, where data isn’t stored like in a relational databases.

And there are countless debates dedicated to the SQL vs NoSQL fight. If you are choosing one over the other, do you know for sure why and what are the potential benefits of each? To help make your decision in choosing the right database for your business a little easier, we’ve highlighted main differences between relational and non-relational databases below:

A critical limitation of a relational database is that each item can have only one attribute. For example, each aspect of a customer's relationship with a bank will be stored as a separate row item in separate tables. All these tables are linked to each other using primary and foreign keys. Whereas, in a non-relational database, key-value pairs allow you to store several related items in one row of data in the same table. For example, all the data about the customer and the bank will be stored together as one record.

Relational databases can be configured and set up to run large-scale operations via data warehousing and hence they cater to a large amount of users who are using relational MPP architectures that support scaling such as Analytics Platform System, Teradata, Oracle Exadata, or IBM Netezza. Data warehouses are used for complex analysis of data and differ from transactional (OLTP) database, whose main use is to support operational systems and provide day-to-day, small scale reporting.

The real challenge of a relational database is lack of scalability when dealing with OLTP applications. This is where non-relational models have an advantage. They can easily distribute data volumes across multiple servers. Each server handles only a small amount of the request thereby improving response time. This is the reason why non-relational databases are the choice for web applications hosted on cloud.

Which one to use?

Non-relational and relational databases are designed to support different application requirements and they typically co-exist in most enterprises. The key decision points on when to use which include the following:

The rise of unstructured “Big Data” is what makes non-relational databases necessary. On the other hand, relational databases are well-suited for datasets that are not likely to expand in near future.

While some may never adopt non-relational over relational databases, many organizations have either already made the switch or are planning for it. We are moving towards increased personalization resulting in non-relational models getting adopted. This fact is exemplified by many of the leading companies today, especially e-commerce companies who concentrate on improving search results through pulling up stored data to suggest products that a customer might need. This has played a significant role in the development of online businesses and truly represents the direction that many companies are heading towards today.