An Inverse Of A Relational Model

Data objects can model relational data or advanced data types such as graphics, movies, and audio. Smalltalk, C++, Java, and others are objects used in object-oriented data. The object-relational is a combination of relational and object-oriented databases. Traditional and advanced data types can be used to construct database management systems. These systems can connect to a company’s website and update records as needed. Database Approach The main purpose of a database is data storage that can be stored and retrieved when needed. A popular common language called structured query language (SQL) is used to store and retrieve data in relational database. This language enables the systems to run a report or modify data or remove the data from the database. A database management system (DBMS) controls all aspects of a database, this is not limited to the creation, maintenance, and use of database. The DBMS ensures proper applications are able to access the database. An important purpose of a DBMS is to maintain the data definitions (data dictionary) for all the data elements in the database. It also enforces data integrity and security measures. Data Models Data models provide a contextual framework and graphical representation that aid in the definition of data elements. In a relational database, the data model lays the foundation for the database and identifies important entities,

Document store: These store complex data structures known as documents, by associating them with a unique key. Documents can contain many key-value pairs and can even nest other documents. E.g. MongoDB,

Structured data follows a specific pattern of organization and is easy to access, manage, and store. It fits nicely into rows and columns of traditional database management systems.

Abstract- This research documents a comprehensive evaluation of the emerging graph databases along with a benchmark study to compare it to the existing relational model. With the ease of the graphical representation brought in with Neo4j, we saw the opportunity to attempt getting details about the various attributes in the dataset and analyze this data to present a statistical view along with its popular counterpart, MySQL. The ultimate goal of this study is to determine whether a traditional relational database system like MySQL, can be replaced completely in production, by a graph database, such as Neo4j.

A relational database is a database that consists of a collection of tables with columns showing entities, and rows showing data. This type of database uses a primary key and foreign key. The foreign key in another table will point to the primary key of a table, and this is how tables can relate to each other. This permits for one-to-one, one-to-many, and many-to-many relationship between the data. An advantage of relational databases includes the ease of adding or modifying new tables and entities without needing to change the structure of the database already in place. Relational database have many features, including indexing, setting data type, and setting validation tests, all these help to ensure data integrity.

Key/Value Database is a type of NoSQL Database. NoSQL Database stands for Not Only SQL Database which means that the database can store heterogeneous data. The Key/Value database does not follow the conventional relational database way of storing the data. Every piece of data that needs to go into the DB, gets a key associated with it. Additionally, few other metadata also gets attached to the data. It stores data as hash table where each key is unique and the value can be string, array of strings, integer etc. Initially, data is stored in in-memory, but after particular time intervals or depending upon some specified condition, data is moved to disk in the form of Shards. Shards are nothing but XML

Relational data is when you can put data in a computer one time and it grows

The tables in relational databases organize data in rows and columns, simplifying data access and manipulation. It is easier for manager to understand the relational model than put all data in one table. Besides, a relational database allows tables to be linked. And the linkage reduces data redundancy and allows data to be organized more logically. In a word, relational database is easier to control, more flexible, and more intuitive than approaches.

Relational database contains data records that do not have a preset of relationships, permitting the user to define his or her relationship when accessing the data. Since users have much control over the data being accessed, relational databases can perform a variety of tasks. Such as defining the database; querying the database; adding, editing, and deleting data from the database; modifying the structure of the database; securing data from public access; communicating within the network; and exporting and importing data (Murthy, 2008).

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

A relational database is designed to comply with a term called normalization. Normalization is a process of organizing tables to minimize the redundancy in the database. The design of a relational database decreases the amount of space the database uses in a system. The relational database uses fields to help reduce redundancy in the tables. Relational designed database use the relational value in fields, an example would be a field for Book_ISBN and a field with Title_ISBN, could be limited to just one field naming the ISBN (Safari).

Key-values stores: Strength: Simplest and easiest to implement. However, one of the weaknesses is that it doesn't perform well when querying or updating a particular value.

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

Data redundancy could be defined as keeping the same piece of data in two separate places within a database or data storage technology. Traditional file-based systems stores the same information in more than one file through which space is wasted unnecessarily. But the DBMS ensure that multiple copies of the same data are not stored by integrating the files to eliminate the redundancy. Sometimes, it is necessary to duplicate key data items to model relationships. Moreover, it is desirable to duplicate some data items to improve performance. Due to above reasons DBMS does not eliminate redundancy entirely.

The modern RDBMS advancements are not capable of supporting unstructured information with ideal space necessity. The plan winds up plainly mind-boggling and is henceforth troublesome for designers. The requirement for unstructured information administration is so annoying with conventional RDBMS arrangements (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). Moreover, RDBMS turns out to be an exorbitant answer for creating light-footed web applications with direct information investigation necessities. NoSQL is developing as a proficient possibility in this situation, which connects the issues related with RDBMS innovation. The market development can credit to creative dispatches of NoSQL arrangements, and collective endeavors by NoSQL sellers and clients. The endeavors of organizations, to enhance their market offerings, are creating the request of NoSQL, as a back-end bolster (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). The emergence of agile software development is creating the demand for NoSQL (Big data in financial services industry: Market trends, challenges, and prospects 2013 - 2018). They offer users much more avenues to accept data in many different forms. NoSQL is adaptable as SQL but offers many more uses that can apply to many organizations.