Advantages And Disadvantages Of Data Storage

Relational Database Management Systems are probably the ones that we are most familiar with in 21st century computer science. Relational databases store

Since 1960 and beyond the need for an efficient data management and retrieval of data has always been an issue due to the growing need in business and academia. To resolve these issues a number of databases models have been created. Relational databases allow data storage, retrieval and manipulation using a standard Structured Query Language (SQL). Until now, relational databases were an optimal enterprise storage choice. However, with an increase in growth of stored and analyzed data, relational databases have displayed a variety of limitations. The limitations of scalability, storage and efficiency of queries due to the large volumes of data [1] [2].

Column family stores: Strength: great way to distribute data globally with high availability. It performs great with very large amounts of data distributed over many machines. Weakness: column oriented databases will be significantly slower when handling weather transactions.

The database used should be open and industry standard to allow easy integration with other applications and easy movement of data in the future. The database

For the purpose of this paper, we are going to focus on these three type of NoSQL database BigTable, Cassandra, DynamoDB.

Relational database management system (RDBMS) have used for many decades. However, these databases are facing several challenges with the requirements of many organizations like high scalability and availability. They cannot deal with huge amount of data and requests efficiently. As a result, famous organizations such as Google and Amazon shift from RDBMS to NoSQL databases. NoSQL databases have several features that overcome issues. This paper explains features, principles, and data models of NoSQL databases. However, the main focus of this paper is to compare and evaluate two of the most popular NoSQL databases which are MongoDB and Cassandra.

In this model, data is stored in sections of columns instead of rows. This is almost an inverse of a relational model. The names of the column need not be predefined, i.e. the structure isn 't fixed, which helps in great scalability and performance. Columns in a row are stored in order according to their keys. A super-column also might be used which is nothing but a column containing nested sub-columns.

The rapid growth in the world of technology has influenced the way we communicate, shop, learn, and share information. The development of technology led database analysts and administrators to find more convenient ways to store the big amount of data. Big data is known as expression in the tech-world. It is defined as a huge collection of data that cannot be managed by relational databases (Moniruzzaman and Hossain 1). So, developers start to use non-relational databases (NoSQL) to arrange and store the Big data. In order to understand how developers solve the storing issue of the big amount of data and provide systems that can sync data between multiple devices, we need to start with a brief background of NoSQL databases to understand Couchbase system. The purpose of this paper is to define NoSQL database, compare it with SQL database, define Couchbase and describe how Couchbase is synchronizing data between multiple devices, especially Couchbase Mobile.

Over many ago relational databases reside most of the data but after the introduction of NoSQL database had changed this procedure. Most of the unstructured data had been sent to NoSQL database. Relational database systems, which showed good performance before the birth of internet and cloud computing era is now unable to control the heat of new technologies. To stabilize this situation new requirements were set to design by RDBMS. To meet these challenges they need highly scalable and unstructured data model with high performance; so they choose NoSQL database (Muhammad Mughees, 2013).

These relationships between different types of data were defined in a database schema, the relational database could be queried with a standard Structured Query Language (SQL). These SQL based databases require a fixed amount of tables, a fixed amount of columns in each table, with each column represent a fixed data type (integer, string, etc). Consequently fields of data stored in each column must comply with the structure of the database and its tables. whatever data you want to store must be known to create an appropriate database schema, this is the concept behind relational databases.

Column-based or wide column NOSQL systems: These systems segment a table by column into column families where every column family is put away in its own records. They additionally permit forming of data qualities. Chart based NOSQL systems: Data is spoken to as graphs, and related hubs can be found by navigating the edges utilizing way expressions Data with the accompanying attributes is appropriate for a NoSQL system firstly, Data volume becoming quickly secondly, Columnar development of data then, Document and tuple data Lastly, Hierarchical and graph data. Data with the accompanying qualities may be more qualified for a conventional relational database management system is On-Line Transaction Processing required atomicity, consistency, disengagement, toughness prerequisites (ACID) then Complex data relationship and Complex question prerequisites [2] Apache Cassandra are example of BigTable-style Databases Oracle Coherence, Kyoto Cabinet is case of of Key-Value Stores. mongo DB and Couch DB is example of document database and neo4j and flock dB is case of graph database. [4]. I have selected document base data modeling to compare and contras with relational data modeling.

STRUCTURE OF DATA: The data structure of a relational database comprises of table structure. Every table is identified by a unique name or label. The data tables are described as the collection of rows and columns. Each row of the table is known as the record and each column is known as the field of the specific data table. All the data sets are well organized and logical linked to each other through definite and unique relationships. A table, therefore can also be defined as the “structured collection of relationships”. The fundamental aim of developing No SQL database systems is to easily and effectively handle vast quantity of data or information in advanced web-scale applications. In order to achieve this purpose, the No SQL systems are designed as the schema-free database systems. There are different modes to define the No SQL databases that typically depend on the requirements of the data that has to be managed. The main No SQL data structures include column database, key-value store database, document store database, graph database and

A key-value database is a type of unstructured database designed for very fast retrieval of information. The data is referred to as the “value” and is linked to by a unique “key” which can be composed of several different data types. It is quite different from a relational database in that it does not store values in tables, rows or columns. A relational database “User” table might look something like this:

of its schema-less structure along with its capability of handling BIG Data. In this paper, we talk

NoSQL Databases also referred as Not only SQL databases. These NoSQL database have these days gained much attention and reputation because of their performance and high scalability. The advantage of NoSQL database is to store efficiently unstructured data. These days use of e-commerce websites, social networking sites etc. has been increased. These usage made to create the need to store the large data. Some companies have adopted NoSQL databases, as their data is growing. Dynamo, Big table, Voldemort, Cassandra are the NoSQL databases that are used by Amazon, Google, and LinkedIn and Facebook respectively. Facing these huge data has become challenging for Relational Database Management Systems. Hence NoSQL database came into existence. Mostly Relational Database Management System satisfies ACID properties, through NoSQL database we can achieve high level of Scalability and performance. As a lot of sensitive data is stored in NoSQL databases security issues becomes growing concerns.