Do some amendment and enhance the given research paper: Table of Content Abstract..3 Action Research.4 Research Methodology

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Do some amendment and enhance the given research paper:

Table of Content

Abstract……………………………………………………………………………………..3

Action Research…………………………………………………………………………….4

Research Methodology and Design………………………………………………………...5

Literature Review: NoSQL Database………………………………………………………7

Proposal…………………………………………………………………………………….7

Iteration 1…………………………………………………………………………..8

Iteration 2…………………………………………………………………………..9

Iteration 3…………………………………………………………………………..10

Iteration 4…………………………………………………………………………..10

Iteration 5…………………………………………………………………………..11

Criticisms of NoSQL……………………………………………………………………….11

Conclusion………………………………………………………………………………….12

Project Plan………………………………………………………………………………….13

Action……………………………………………………………………………………….15

Observation………………………………………………………………………………….16

Reflection……………………………………………………………………………………17

References……………………………………………………………………………………19

Abstract

In the world of technology for four decades now, many data handling organizations have been using rational databases model in storing, managing and retrieving data. But over a time this model has not been sufficient and convincing enough to be used in storing data due to its low scalability, and poor performance. With this, there is an increasing interest in NoSQL technology due to its ability to be used in a wide range of functions. This study is focused on trying to help our information systems managers bang engineers by surveying and creating an up to date NoSQL models. We also go ahead and identify the case scenarios where this technology was useful and beneficial as well as the suitability of its various engines.

Keywords: NoSQL Technology, Structured Language Query, Database

Action Research

For nearly forty years the use of action research has been the leader in the modern day computing needs. This model was seen to be the solution for all the management of data systems(Vaish, 2013). However in time due to large amounts of data being handled in the web systems, there has led to establishment of a number of NoSQL databases particularly for the Big Data Systems.

NoSQL came into existence in the first place in the year 1988 as term which was used to refer to a relational database that lacked a Structured Query language (SQL). In 2009, the same term was brought back and used to refer to new highlighted non-rational databases such as the dynamo and the BigTable and has then been used to date without a specific definition (Orend, 2010). In spite of its recurrence in technological literature, the term SQL is very broad and incorporates very discrete systems of database(Sullivan, 2015). In general, this technology’s model uses different approach in storing and accessing data as compared to the former relational database systems.

There are nearly a hundred readily available databases based on NoSQL, and for each, different functions are assigned to them. They are further categorized into four in accordance to their model and storage of data. These are: Column Stores, Key Value Stores, Document Stores and Graph Database. These classifications are founded on the basis of their different kinds of solutions they offer for various case scenarios. There is no more all fit in one model as used by the rational database technologies.

A lot of researches have been done in comparing the relational and non-relational databases majorly with respect to their performance in their applicable functions. But in most cases performance has been used as the only quality attribute which is put into concern in developing enterprise systems. There has been a non-comprehensive assessment of NoSQL technology which has been a matter of concern to organization’s quality attributes of software (Hann & Le G Du J 2011). The goal of this study is to bridge this gap through making an identification of the best NoSQL database which will better the promotion of other better features and in turn becoming a benchmark for data software managers and engineers.

Research Methodology and Design

The design and methodology of doing this work is focused on answering the question of whether there is adequate knowledge on beneficial attributes of NoSQL in facilitating software management process decisions. Research has shown that there is no literature that serves as a guide to identifying the quality attributes of NoSQL databases. Thus in the methodology, the main focus is answering the question.

At the start of the work, the various beneficial attributes were identified in order to evaluate NoSQL databases. There are a wide range of attributes and yet others are even universal for all other software projects, and a number of them are very much associated to the topic of study; models of storage, database systems applications in web (Hann & Le G Du J 2011). Therefore this has led in selecting the following beneficial attributes to be put into evaluation, they are: scalability, reliability, read and write performance, time of stabilization, consistency, its durability and availability. Once the attributes are identified, a research on which systems of NoSQL were mostly used by most data handlers in order to come up with a comprehensive set of NoSQL databases is done. With this, MongoDB, Voldemort, Cassandra, Aerospike, and Couchbase were identified for evaluation.

A further survey was made on the existing literature in order to put into evaluation the selected attributed qualities of the earlier mentioned databases. The already available evaluations on the quality attributes were also taken into account in the survey carried out (Hann j Haihong, Le G Du J, 2011). In carrying out the survey, the articles containing outdated information were least considered. Also taken into consideration are each NoSQL systems’ architecture (Tiwari, 2011).

In the methodology as well, each NoSQL database is given a description in terms of the their key attributes and features basing on the CAP theorem, guaranteed consistency, configurability, ,mechanisms of control, schemes of partitioning and other key mechanisms (Stonebraker, 2011). This ensures that there is a fine-tuned and consistent property.

Finally after gathering all the information, the results of the evaluations were presented in summary tables that gives an indication of which databases provide the best suit for every quality attribute which are hoped to help the software managers and the engineers in the process of decision making when required to make a choice of various NoSQL databases basing on their attributed qualities (Fowler & Sadalage, 2012).

Literature Review: NoSQL Database

NoSQL solutions have been developed to handle various challenges encountered when dealing with applications found in big data. These applications store large sets of data in the database. In some cases, the traditional Rational Database Management System (RDMS) ensures data integrity and transaction consistency at the expense of a complex management and a rigid data schema (Bugiotti, Cabibbo, Atzeni, & Torlone, 2014). In business operation and financial applications, data integrity and consistency are important although the organization may not always need them. The objective of this project is to establish a particular picture concerning the evolution of NoSQL and mechanisms as well as the benefits and limitations of the main NoSQL data models and frameworks in business performance. For this purpose, it will be imperative to examine criteria including performance, scalability, security, consistency, fault-tolerance mechanisms and analytical models.

Proposal

Enterprises across all companies are challenged by the task of ensuring scalability of the massive size of data as well as keeping database models simple and flexible (Cudré-Mauroux, et al., 2013). NoSQL has emerged in response to this problem by offering new methods for storing data. The NoSQL ecosystem has thrived with various software contributions appearing under this application. As more businesses have implemented the NoSQL solutions, a distinctive set of criteria has evolved that can assist the IT specialists to widen the development of enterprises regarding data storage (Gajendran, 2012). This proposal will focus on four iterations with an aim of minimizing the challenges that the business organizations encounter. The plan for solving this problem will be based on the use of NoSQL database. This methodology will perform various functions that include:

Serving as an online processing database with the aim of becoming the primary data source or operational data store for online applications.
Using the stored data in main source system for batch analysis, real-time and business search operations.
Offering a flexible schema design that can be transformed without service interference
Accommodating structured, non-structured and semi-structured data
Handling large amount of data stored by involving data velocity, volume, variety, and complexity.

Iteration 1

NoSQL databases are organized in a different way with data in NoSQL being greatly de-normalized, and existing in structures organized in various formats such as a document, columnar, graph or key-value store. Arguably, most NoSQL databases do not follow the standard Code relational model where data is normalized to a third form. According to Mohamed, Altrafi, & Ismail (2014), NoSQL databases perform best when dealing with data that is either impossible to store in a Rational Database Management system or data that performs very poorly when retrieved in a rational manner. Such a problem can be examined as transversal in a social network. Interestingly, this challenge can be solved in a relational way although it becomes unmanageable with the constant increase in data (Tauro, Aravindh, & Shreeharsha, 2012). The following table lays some of the primary attributes that need to be considered when evaluating NoSQL databases.

Data Model	Performance	Scalability	Flexibility	Complexity	Functionality
Key-value store	High	High	High	None	Variable(None)
Column-store	High	High	Moderate	Low	Minimal
Document-store	High	Variable(high)	High	Low	Variable(low)
Graph database	Variable	variable	High	High	Graph theory

Iteration 2

Pokorny (2013) argues that NoSQL data storages may be the optimum choice for solving big data challenges or for data circulated across numerous servers in a web environment. However, not all enterprises run with big data and not all of them need web scalability. Indeed, there are relatively few works illustrating the application of NoSQL in a medium or small-sized business environment where the traditional usage of SQL databases are more frequent (Tauro, Aravindh, & Shreeharsha, 2012). This statement investigates how a medium-sized company may successfully use NoSQL data storage solutions and benefits. With this view, the primary research questions that will be asked are:

What are the advantages of using NoSQL data storage in the enterprise environment?
How does the choice of data storage influence the flow of the application development and architecture of the system?
How easy is it to incorporate a new solution with the legacy one when applying NoSQL databases?

Iteration 3

The global research indicates that the business world is experiencing enormous change due to the transition of the companies to the industrial world. This move is powered by the internet and other technologies such as social media, cloud, mobile, and big data (Vilaça, Cruz, Pereira, & Oliveira, 2013). All these techniques form the heart of a business operation because they are the central means by which the companies communicate with the clients and run more of their business. In fact, the experiences that firms deliver through these applications mostly determine the satisfaction and loyalty of the customers.

Iteration 4

When the database of a company is designed using the above techniques, the methods must support a large number of frequent users, be accessible, and handle semi and unstructured data. In the same way, they must rapidly adapt to shifting needs with consistent updates and new structures as well as obtain highly receptive experiences to an internationally scattered base of users (Vilaça, Cruz, Pereira, & Oliveira, 2013). However, developing and running the applications associated with these characteristics have created a new set of technology needs. For instance, the new enterprise technology architecture must be agile. The architecture should also implement an approach to real-time data management that can accommodate unprecedented levels of speed, data variability, and scale (Zaki, 2014). The inability of relational databases to meet these new requirements has; however, forced the enterprises to turn into NoSQL database technology.

Iteration 5

Insofar, NoSQL databases are built to offer high availability at the price of losing Atomic, Consistent, Isolated, Durable (ACID), and durables guarantees of the traditional databases. This purpose evolved in exchange for keeping a weaker Basic, Availability, Soft state, Eventual (BASE) consistency feature (Vilaça, Cruz, Pereira, & Oliveira, 2013). The researchers have summarized the main categories of NoSQL databases as Document stores, key value stores, column family stores and graph databases. The most commonly used type is the document model as illustrated in the representation below.

Criticisms of NoSQL

Although NoSQL development is impressive, there are ideological, structural and other constraints in NoSQL that must be handled. Identifying these problems will let companies make appropriate decisions and build reliable solutions for their businesses. One of the main disadvantages of this system is redundancy (Gajendran, 2012). That is to say, the related data such as customer information and street address are stored in the same place. As a result, the data can be duplicated throughout the database. Another challenge is the lack of ACID transactions (Pokorny, 2013). Without this operation, it becomes difficult for financial or sensitive data to be guaranteed in a valid state. Consequently, the economic data may disappear until the situation of the database becomes consistent. Another shortcoming is immaturity (Zaki, 2014). This challenge is viewed concerning bad support, questionable reliability and lack of documentation.

Conclusions

Overall, it can be noted that the firms employ the power of NoSQL databases when they need to save data that does not bend naturally into a stable system provided by rational databases. It becomes difficult to design such database since it needs a lot of knowledge and experience. The cost of maintenance of such databases can as well rise. Another important fact is that all companies implementing the NoSQL system enjoy the benefit of retrieving data in the efficient and instant way. Data availability is also a major concern of industries that deal with large sets of data. Quick retrieval of data helps in avoiding data congestion. Even so, the ability of the database to scale is one of the significant features that NoSQL databases need to provide. Lastly, an important property of common problem is how rapid it is possible to model, operate and deliver such database. In the developing business environment, it is highly imperative to form new features, offer new values, and create new systems for customers in an efficient manner.

Project Plan

The project will build on recent NoSQL funded work at the organization to develop, test, and implement a state of the art research data management infrastructure(Abramova, Bernardino, & Furtado, 2014). The researchers have planned to work with the challenging needs of their engineering research as well as their industry partners. To achieve this obligation, they will apply their experience and understanding of developing organizational wide-data-driven services to the implementation of a personalized, resilient, scalable, and secure research data infrastructure(Chen & Liu, 2014). Additionally, they intend to apply a proven approach to the organization of institutional through the proposed application of flexible, quick, schema-less database technology.

This project will help in creating flexible services for capturing, saving, preserving, and sharing research data in real time across internal research teams(Deka, 2014). A personalized web interface for particular researchers’ profiles and public discovery will also be established. To maintain and extend the application of this technology across the organization, the researchers will ensure that the appropriate institutional strategy, support for academic staff and research students as well as institutional policy is developed and approved(Doulkeridis & Nørvåg, 2014). The project plan will include the users in the organization and their external research partners as well as staff from Center for Educational Research.

The researchers have also planned to build on their previous work around the management and access to the data driven services at the organization. Throughout this approach, they aim to enhance their understanding of the issues around research data management, develop a business plan, refine the use of agile methods, preserve research data, and implement appropriate policy for the sharing of the research data. For effective performance of the NoSQL database, the researchers will use an agile approach to develop orbital based on regular active input from users(Mohamed, Altrafi, & Ismail, Relational vs. nosql databases: A survey, 2014). To support the NoSQL program, it will be important to consider distributed source-code respiratory for project and personal task management.

For this project, the tea has decided to use its institutional get satisfaction account for supporting and managing user request ad feedback. Each of these approaches is integrated at the Application Program Interface level to tie customer feedback based on project task(Nayak, Poriya, & Poojary, 2013). Besides NoSQL software, the researchers have planned to use other collaborative programs such as project blog and google doc while studying how bigger firms store data. Since the management frequently use an agile method to project management, more task will be performed iteratively depending on close engagement with the users. For that reason, the requirement analysis, documentation and dissemination as well as technical development of the deliverables will be involved(Pokorny, NoSQL databases: a step to database scalability in web environment., 2013). However, a required analysis and implementation plan will be produced within the first quarter of the year as per the program required deliverables.

To attain this plan, the researchers will recruit more than two developers. Dissemination will be both formal and informal. More forma dissemination will occur through the use of press release, case studies, workshops, and journal articles(Shen, Yu, Wang, & Kou, 2013). Due to the relevance of NoSQL database in the organization to the proposed project, the design of the pilot infrastructure will follow a review of analysis, synthesis work and recommendations of the research. Perhaps, the NoSQL program has synthesized much of the study relating to the research data management. Subject to the researchers needs, they anticipate to re-use numerous technologies that have been implemented. Such projects include Mongo DB, a database used by companies such as LexisNexis. A document oriented NoSQL database such as Mongo DB will be expected to offer flexibility in data object; for instance, survey results, tabular data and images(Tauro, Aravindh, & Shreeharsha, Comparative study of the new generation, agile, scalable, high performance NOSQL databases, 2012). This will be done without developing a schema beforehand.

Action

This survey has focused on providing business managers with knowledge of NoSQL databases and of the risks associated with the business. In contrast, the research has involved non-empirical study based on an extensive literature review of related aspects to NoSQL(Zaki, NoSQL databases: new millennium database for big data, big users, cloud computing and its security challenges, 2014). Based on the literature review, the characteristics, and key drivers and the benefits of NoSQL databases have been identified. The NoSQL also abandoned the rigid model because it became exceedingly hard for databases to accommodate new types use cases for the data. The web business required data models that could evolve with their changing needs without any downtime or relational model.

When new kinds of data become available in the entire sources that have been developed with the presence of big data era, a flexible data model could be effective to integrate and leverage the current data(Abramova, Bernardino, & Furtado, 2014). Modern NoSQL databases have provided a data model that can be adjusted without the normal operation and availability disruption. Due to the data requirement of applications not being equal, a large number of NoSQL databases have been formed to solve the various data needs. The different NoSQL databases are not one-size-fits(Chen & Liu, 2014). Instead, they are specialized to be applied for particular problems related to data. For that reason, the data needs of the application should determine the type of NoSQL database best suit the specific situation. As illustrated in the previous areas, the available data in the world are developing to massive levels.

Observation

NoSQL databases can provide firms with many benefits although they contain some risks. As observed, the lack of knowledge among the decision makers of business pertaining NoSQL databases can result in unaddressed risks and missed opportunities. This study has identified the key drivers, characteristics and benefits of NoSQL databases with an understanding of the subject(Nayak, Poriya, & Poojary, 2013). In essence, the discovery has identified the business imperatives associated with NoSQL databases. All these observations can help the business to determine whether the program might be a viable solution. Additionally, it aligns business and information technology objectives.

The survey has also identified the primary strategic and operational risks related to Information Technology. The identified challenges were mapped to the process of control objectives for information and related technology to create awareness for the business on the highest risk parts and the associated focus regions(Deka, 2014). As observed, the limitations of relational database model as a solution to database has become evident due to the rising data and infrastructure requirements of the large companies. Some of the reasons behind inadequacy of the relational database management system include

The relational model is too rigid to model web data
Traditionally, rational database management system do not support the evolution of schema; therefore, it lacks the required flexibility
The RDBMS path lengths are inaccessibly long and the involving cost is too high.
The data consistency needs of the RDBMS are too stringent.

Amazon and Google which also experience the challenge of relational database have responded by designing their database solutions. Besides, the researchers observed that the characteristics of NoSQL are defined as using a non-relational data model that is designed for distributed processing and horizontal scalability(Mohamed, Altrafi, & Ismail, Relational vs. nosql databases: A survey, 2014). This characteristic allows for less strict regulations pertaining adherence to database schema and reduced data consistency. Compared to RDMS, NoSQL database is a new idea that has not been adopted widely with many NoSQL vendors still being start-ups.

Reflection

From an individual viewpoint, it can be noted that the performance of any system including a DBMS has always been a significant issue to consider before implementation. NoSQL developers tend to market their database systems because it provides increased performance compared to traditional relational database. One of the goals that was set and attained by google was its high performance distributed storage system. Cassandra, a data store that was created by Facebook to trigger a new search feature has achieved greater speed of about 2500 times faster than MySQL. Amazon Dynamo is however, designed to make trade-offs between availability, cost-effectiveness, performance and consistency. From the research findings, no NoSQL databases efficiently use supplied indexes and computer memory to boost the performance.

The performance increase that can be achieved while using NoSQL database makes it worth for organizations to consider them as a solution to database. According to the study, an optimized Rational Database Management System is capable of outperforming NoSQL databases in some instances(Nayak, Poriya, & Poojary, 2013). Even though some NoSQL database implementations have proved to be reliable while delivering high performance, an optimized rational database management system is still significant. As previously mentioned, many NoSQL databases are open source. Therefore, the cost of licensing that are associated with commercial relational databases can be lessened while transforming to a NoSQL open-source alternative.

The commodity servers that NoSQL databases use to scale horizontally are also less expensive compared to the large commercial servers of traditional relational database. These servers are warranted in case the scale of relational database becomes very high(Zaki, NoSQL databases: new millennium database for big data, big users, cloud computing and its security challenges, 2014). Based on this chapter’s discussion, it is clear that NoSQL databases are more suitable for business based on internet. The values of NoSQL databases can provide a better fit for the needs of particular internet based businesses. The findings show that NoSQL databases can be adopted by firms of all sizes(Abramova, Bernardino, & Furtado, 2014). An enterprise can benefit from using a NoSQL database as a hybrid solution with a relational database. However, this database might not replace every relational database of a business. NoSQL databases can therefore be considered an additional tool to achieve the business objectives.