A Study Of Nosql Implementation Techniques

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,

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.

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

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].

Graph database: Strength: designed for data whose relations are well represented as a graph and has elements which are interconnected. Graph databases are well-suited to irregular and complex structures. Weakness: Relationships are stored at the individual record level and uses more

Abstract – With companies such as Facebook and Google producing large volumes of data, known as Big Data, the popularity of NoSQL databases has risen in the past decade as traditional relational databases cannot handle the vast amount of data as it was not designed to effectively manage such a large data collection. The following research paper gives an introduction to non-relational databases otherwise known as NoSQL. It defines what a NoSQL database is, the origins of its existence and the various types of NoSQL databases. It goes on to discuss the advantages and disadvantages of non-relational databases and the reason companies in the past decade are selecting to implement these databases over traditional relational databases.

A key-value store database has a set of keys and values, and each value is associated with a key. The implementation of key-value store database is actually a distributed hash table (Stonebraker, 04/2010). Key-Value Stores(KV), which are normally known as a model of NoSQL databases, are widely deployed for data operation and management in purpose of enhancing Internet services due to better scalability, higher efficiency and more availability than existing relational databases systems (Wang, et al., 2014). Because KV stores sacrifice relation model in exchange for fast writing, and they are often featured with simple methods like “put()”,”delete()” and “get()”.

The need to store and evaluate data is a perpetually growing field in the world of information systems. From the days of using flat files to very large database management systems that store petabytes of data in real time, the practice of building information from data continues to evolve. Today, the relational data model is quite ubiquitous and is used in a plethora of information systems ranging from accounting systems, banks, retail business, and scientific usage. It is important to understand the concepts involved in data modeling for a relational database management system in order to build an effective and efficient system.

A graph database represents data and relationships between this data using concepts from graph data structures like nodes, edges and properties. Nodes represents the data entities, properties represent information about the nodes and edges which connect two nodes or a node and a property represent the relationship between the connected elements. [1]

A lot of speculations have been raised on whether modern NoSQL database is vulnerable to NoSQL attacks or not. The aim of the paper was to research on this issue and after thorough, the paper identified that modern NoSQL database is vulnerable to NoSQL attacks. The problem in the research paper was to identify how modern NoSQL database is vulnerable to NoSQL attacks. Use of JSON to inject NoSQL attacks, lack of admin authorization use of clear text and use of PHP applications to inject NoSQL attacks on the database are some of the reasons that were identified to cause the big problem of NoSQL attacks in the modern NoSQL database. However, solutions to the above problems were identified in the research. Some of these solutions include use of encrypted texts, use admin passwords, input validation and Bind the NoSQL process to only a single interface/IP among others.

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.

For example, Facebook which is the most popular social networking website recently announced their adoption of a NoSQL based graph data store for efficient storage of user data. In other words, NoSQL has already made its way into the enterprise. However, just like every other widely accepted technology, NoSQL has its own set of advantages and disadvantages. It is important for an enterprise to quantify the pros and cons of a particularly new database technology against the already existing solutions based on their custom requirements. For example, legacy enterprise applications may require extensive community support from their database vendors. Moreover, traditional relational database vendors such as Oracle have already established themselves for providing excellent support. On the other hand, NoSQL has been rapidly growing since the past few years and is consistently evolving in terms of big data handling, data warehousing and lesser complexity. Hence, there is a need to study the current market of data stores based on the most popular NoSQL data stores and how well they fair against the widely accepted traditional database systems. This requires a study of the commonly used NoSQL data stores.

MongoDB is a NoSQL document database that is scalable and flexible but allows querying and indexing. MongoDB is free and open-source, so it can be changed to suit any needs. (MongoDB, 2017b)

The purpose of this report will be to understand what a NoSQL (Not Only SQL) database and document database is, specifically MongoDB while looking at the document database.

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.