Big data is a term that specifies a large amount of data – both structured and unstructured. The Internet, smartphones, heavy use of social media, increased digitization, and other technologies making Big Data bigger and more turbulent every day massive volumes of varied and unstructured data—flooding in at unprecedented speeds—are striking today’s businesses. People connected to the World Wide Web and the amount of time that they are spending on the web for different applications and services is continuously increasing. Several mobiles and web applications may account for billions of users who will give birth to a lot of data. But the amount of data is not important, what the organizations do with that data matters. Big data can be analyzed and processed for insights for better decisions and to plan business strategies. This data is stored and processed on the basis of structured and unstructured – needs database systems.
Conventional Relational Database Features
The fundamental database, like MySQL, Oracle Express Edition, and MS-SQL that uses SQL, all are the Relational Database Management Systems that make use of relations to store data. The data gets organized into one or more tables (or relations) of columns and rows, it correlates with the help of some common characteristics that are present in the Dataset and the result of this is referred to as the Schema of the RDBMS.
Relational databases (RDBMS) such as Microsoft SQL Server and Oracle have ACID (atomicity, consistency, isolation, durability) properties that assure database transactions are processed reliably, durability and data integrity. But, these are costly features which come with licensing fees and data speed.
Until now, these relational databases were largely used. SQL databases such as Oracle, Microsoft SQL Server, and MySQL were only having a monopoly. But that is notably changing. In the last few years, the increased need to process higher volumes, velocities, and varieties of the data at a rapid rate has altered the nature of data storage needs for application developers. NoSQL Database, also known as ‘Not Only SQL’ is an alternative to SQL databases become more popular, MongoDB and Apache Cassandra and HBase have enjoyed exponential growth in comparison to their RDBMS counterparts.
Need of NoSQL
Relational Database Management Systems based on SQL are Schema-Oriented, it scales data vertically. The structure of data must be in well-known formats to get well-suited to the schema. The predefined schema that uses SQL may include applications like, Order Processing, Flight Reservations, Banking Processes, and much more. SQL can’t process unpredictable and unstructured information. Big Data applications demand an occurrence-oriented database which is highly flexible and operates on a schema-less data model.
Enhancing of SQL Databases needs an implementation of new hardware, tends to costly deal for processing large size of the data. As the size of the database or number of user increases, RDBMS using SQL suffers from serious performance-congestion – making real-time unstructured data processing difficult.
There is a requirement of a database technology that can furnish 24/7 support for storing, processing and analyzing this data. This outbreak of data is proving became too large and too complex for conventional relational databases (RDBMS) to handle on their own. RDBMS utilizes Structured Query Language (SQL) as the language for querying and maintaining the database.
RDBMS is not always the best solution for all situations as it cannot be expedient the increasing growth of unstructured data. As the data processing requirements expand exponentially, NoSQL is a dynamic and a cloud friendly approach to dynamically process unstructured data with ease. IT professionals generally debate the benefits of SQL vs. NoSQL but as the business data management needs are increasing, NoSQL is becoming the new era of the big data management. Hence, top internet companies like Amazon, Google, LinkedIn and Facebook has initiated Big Data NoSQL databases to overcome the drawbacks of RDBMS.
Supreme Characteristics of NoSQL Database
NoSQL Database (Not Only SQL) is an alternative or may be a replacement to SQL database which does not need any kind of fixed table schemas, unlike the SQL. NoSQL is a database technology readily accepted by Cloud Computing, Big Data, the Web and the Big Users. It helps them to overcome the drawbacks of RDBMS. NoSQL commonly scales horizontally and this avoids major join operations on the data. It can be specified to as structured storage which consists of a relational database as the sub-set.
NoSQL Applications for Big Data
HBase for Hadoop, a popular NoSQL database is largely utilized by Facebook for its messaging application and also used by Twitter for generating data, logging, storing, and monitoring data around people search (HBase is a NoSQL database model runs on Hadoop Distributed File System).
MongoDB is another NoSQL Database model used by CERN, a European Nuclear Research Organization. LinkedIn, Concur, and Orbitz use the Couchbase NoSQL Database for various data processing and monitoring purposes.
This stiff rise in adoption of NoSQL does not suggest that the dying of the traditional data warehouse is hand-writing-on-the-wall. Though, it does show that many organizations and application provider are turning to NoSQL as a more cloud-friendly solution to their big data problems.
Big Data demands infinite data processing at a rapid rate with minimal costing that refers to only one option of NoSQL database model for increased data velocity, growing data variety, and exploding data volumes coming into the database from different sources, it urges NoSQL databases like HBase, Couchbase, and Cassandra which can withstand for these requirements of Big Data applications.
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