A Survey On Nosql Database And Relational Database

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

There are a lot of system requirements and assumptions made in this paper. The query model is assumed to have simple read and write operations to data nodes that are identified uniquely by a key. This assumption is made based on the fact that most of the amazon applications does not require a relational schema and can work with simple queries.

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

Provide reasoning to support the use of the NoSQL database as the database of choice to solve the problem faced by TWC. Identify one strength and one weakness for each of the other three kinds of databases to solve the problem for TWC.

Some people believe that the answer to challenges posed by big data lie in a relatively new group of non-relational data storage and management products known collectively as NoSQL. However, NoSQL system development is different from traditional data warehouse development in that it is application driven. This has led some pundits to postulate that NoSQL represents a new paradigm in data warehouse design, where highly specialized data silos will replace the traditionally integrated data warehouse. Therefore it is reasonable to ask, should NoSQL be used to build big data warehouses? If yes, then should integration be discarded in favor of autonomous, application driven data silos?

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

In Nowadays, there are two major of database management systems which are use to deal with data, the first one called Relational Database Management System (RDBMS) which is the traditional relational databases, it deals with structured data and have been popular since decades since 1970, while the second one called Not only Structure Query Language databases (NoSQL), they are dealing with semi-structured and unstructured data; the NoSQL types are gaining their popularity with the development of the internet and the social media since April 2009. NoSQL are intending to override the cons of RDBMs, such as fixed schemas, JOIN operations and handling the scalability problems. 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 database (MySQL). MySQL, it is being another name for Relational Databases and it has been used for a long period time until now. However, with the emergence of Big Data there was clearly a need for more flexible databases. Facebook 's Graph Search using 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 compare between MySQL and Neo4j based on the features like ACID, replication, availability and the language that is used in both of

MongoDB is one of numerous cross-stage archive situated databases. Named a NoSQL database, MongoDB shuns the customary table-based social database structure for JSON-like archives with element constructions (MongoDB calls the organization BSON), making the combination of information in specific sorts of utilizations less demanding and quicker. Discharged under a mix of the GNU Affero General Public License and the Apache License, MongoDB is free and open-source programming.

NoSQL databases are a significant departure from the relational model that has dominated the business world for the past few decades. Standing for “Not Only SQL,” these products are all some variation of a non-relational, key-value pair database, and they are becoming very popular with companies that use Big Data and prioritize speed or availability over consistency of data.

The weakness of the relational database unfolded by the rise of web-driven application (Lake and Crowther, 2013; Dede et al., 2013), whereas non-relational database gained their popularity (Li and Manoharan, 2013; Parker et al., 2013; Prasad and Gohil, 2014). However, since it was believed that a relational and a non-relational database had a different function, therefore Parker et al. (2013); Tudorica and Bucur (2011) stated that those databases were not comparable. Relational database appropriates for modest structured dataset, while non-relational database suitable for large unstructured dataset (Parker et al., 2013).

Answer: NoSQL DB is document based DB and represented in collection without solid structure key-value pairs, documents, graph Db or wide-column stores and has not predefine schema, use Dynamic schema. NoSQL DB is horizontally scalable that will increase amount of DB servers in the pool of

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.

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

The Apache-Hadoop open-source program that provides a layer of software that can turn a grid of servers into a single unit has become known as NoSQL, or Not-Only SQL database. It provides a parallel storage and processing framework to run MapReduce, an application module that runs in two phases, first mapping data then reducing or transforming it. Using the HDFS or Hadoop Distributed File System, huge data sets are spread across servers, thus enabling programmers to write application modules and run them in parallel on the same cluster that stores the data, thus using the power and capacity of all the CPUs and hard drives. The advantage of Hadoop is that it processes large amounts of data in seconds, one

Currently, there are two major of database management systems which are used to deal with data, the first one called Relational Database Management System (RDBMS) which is the traditional relational databases, it deals with structured data and have been popular since decades from 1970, while the second one called Not only Structure Query Language databases (NoSQL), they have been dealing with semi-structured and unstructured data; the NoSQL term was introduced for the first time in 1998 by Carlo Strozzi and Eric Evans reintroduced the term NoSQL in early 2009, and now the NoSQL types are gaining their popularity with the development of the internet and the social media. NoSQL are intending to override the cons of RDBMS, such as fixed schemas, JOIN operations and handling the scalability problems. With the appearance of Big Data,