Advantages And Differences Between SQL And Nosql

In order to overcome these limitations, a new database model known as Not Only SQL (NoSQL) database emerged with a set of new features. The main objective of NoSQL is not to discard SQL, but to be used as an alternative database data model for new features [1] [2] [3]. NoSQL database increases the performance of relational databases by a set of new characteristics and advantages. In contrast to relational databases, NoSQL databases introduced an additional feature that provides flexible and horizontal scalability and taking advantage of new clusters. The rise of NoSQL provides cost-effective management of data in modern web applications. With its new features, NoSQL can be used with applications that have a large transaction, and require low-latency access to huge datasets, service availability while

The wider insight about relational and non-relational database performance, particularly MySQL and Hadoop was gathered through the literature survey. By read textbooks, reviewing academic journals and research papers, I founded a gap in the performance of relational database compare to the non-relational.

One size fits all. The developers go to for all data. You need only a relational database. This is the false assumption that you will see when it comes to database models. The relational database model is great for data that normally can fit into a table, or shows relationships between data, but not all data falls into that category. There are a few options for these situations. You can use an object-oriented database, a hierarchical database, a network database, and a flat-file database.

Although there are many advantages but the DBMS may also have some minor disadvantages. These are:

Tracking the concept of Big Data management from Relational Databases Management Systems to the current NoSQL database, this paper surveys the Big Data challenges from the perspective of its characteristics Volume, Variety and Velocity, and attempts to study how each of these challenges are addressed by various NoSQL systems. NoSQL is not a single system that can solve every single Big Data problem; it is an eco-system of technologies where different type of NoSQL databases are optimized to address various types of big data challenges by providing schema-less modeling and automatic

The Relational database and the No SQL database are both appropriate database methods depending on the way they are being implemented and the purpose of the business for which they are being incorporated. However, both the database approaches have distinct wide variety of characteristics, based on which they can be compared and contrasted in the following way.

NoSQL databases are databases designed to run on clusters of computers/servers, built for the ever-increasing data storage needs for websites. Devised as a way of scaling databases horizontally which is a challenge with traditional relational databases. Scaling horizontally is the ability to add more computers/servers as nodes to a database. These “clusters” work well with write-heavy systems and allow increase storage and processing power limited only by the number of connections you can have on the network. Defined as No-Schema, No-SQL data structures mean they are not limited to the original data structure. Objects and fields etc can be implemented at

This is where NoSQL systems have been created to solve the data management challenges posed by Big Data. NoSQL is not a single system that can solve every single Big Data problem

NoSQL is able to address the massive traffic loads experienced by database servers at corporations that specialize in data processing like Google, Facebook and Amazon. NoSQL technologies can provide near constant availability, massive user concurrency and lightning fast responses. There are four primary NoSQL database implementation types being used today: document based, wide column (or columnar), key-value and graph. The different properties of SQL and NoSQL databases will be examined and an overview of each NoSQL implementation type along with an example will be given.

SQL has dominated databases for a considerable length of time. The shared database show began to ascend in the 1970s and promptly grabbed balance. Its usage been in existence for forty years and sometime later, SQL is so far, the most used sort of database. As shown by db-engines.com, the four of the leading five most prominent databases are social; the main NoSQL database to get through the best five is MongoDB, which has overwhelmed PostgreSQL's fourth-place. A part of the best locales out there uses SQL to inquiry their information, including Facebook and Airbnb. NoSQL will be around in the future because it reflects the ability to give significant functionality, and performance benefits for a

NoSQL Databases are being used in the social media applications and big data processing based portals in which huge, heterogeneous and unstructured data formats are handled. NoSQL Databases are used for faster access of records from the big dataset at back-end. The AADHAAR Card implementation in India was done using NoSQL Databases as huge amount of information is associated including Text Data, Images, Thumb Impressions and Iris Detection. Any classical database system cannot handle the dataset of different types (Image, Text, Video, Audio, Video, Thumb Impressions for Pattern Recognition, Iris Sample) simultaneously.

As there is a rise in data volumes, the manageability of data and storing these huge volumes of data became a cause of concern to most of the organizations. It was during this period when Number of SQL or more popularly NoSQL was introduced, to process these large amounts of data efficiently and effectively. For this purpose, various Data Store categories were developed, based on the different data models. Some of the categories are:

In this paper, we will review one of the graph database (Neo4j), which the graph database is part of the emerging technology that is called NoSQL and compared it with one of the traditional relational databases (MySQL). MySQL, it is being another name for Relational Databases and it has been used for a long time period until now. However, with the emergence of Big Data there was clearly a need for more flexible databases. Facebook 's Graph Search use Neo4j, a graph database, is an application which clearly displays how relationships need to be modeled in a more efficient and sophisticated manner than using conventional relational models. In this paper, we will make a comparison between MySQL and Neo4j based on the features like ACID, replication, availability and the language that is used in both of them.

With the appearance of Big Data, there was clearly a need for more flexible databases. In this paper, we will review one of the graph database (Neo4j), and compared it with one of the traditional relational databases (MySQL) based on the features like ACID, replication, and the language that is used for both of them. MySQL is being another name for Relational Databases and it has been used for a long time period until now. And Neo4j which is a graph database and it is a part of the emerging technology that is called NoSQL is now trying to prove that there is a need for NoSQL usage.

Amazon DynamoDB is NoSQL database, it is famous for its cloud base and speed. It is agility to many data models.