This document discusses the suitability of NoSQL databases for interactive applications. It notes that traditional databases do not provide the necessary scalability and performance for interactive applications that require reading and writing huge amounts of data swiftly. NoSQL databases are better suited for these tasks as they are scalable, fast, and robust. The document provides an overview of NoSQL databases and how their flexible schema, high performance, availability, and ability to scale horizontally make them a better fit than traditional databases for modern, large-scale, interactive applications.
The growth of data and its effi cient handling is becoming more popular trend in recent years bringing
new challenges to explore new avenues. Data analytics can be done more effi ciently with the availability of
distributed architecture of “Not Only SQL” NoSQL databases.
NOSQL Database Engines for Big Data Managementijtsrd
We are living in the digital world and last two decades have seen significant expansion in the information on internet technology. In present digital world the IOT is most popular term means computers, mobile phones and physical devices like sensors are connected to internet. With the rapid outreach of internet it is very important to focus on technological advancements for managing huge amount of data with easy access. Mrs. Yasmeen "NOSQL Database Engines for Big Data Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18608.pdf
Synopsis: Modern enterprises anticipate business requirements and work proactively to optimise the outcomes. If they don’t renovate or reinvent their data architectures, they lose customers, and market share. So my talk will be in detailing the importance of data architecture, architectural challenges if is not addressed and a case study - the learnings and success story by fixing the issues at the root - at the data storage & access.
Target Audience: Principal Software engineers & Architects
Key Takeaways: Importance of Modern Data Architecture, PostgreSQL & JSONB
I have given a talk @ https://hasgeek.com/rootconf/elasticsearch-users-meetup-hyderabad/
The growth of data and its effi cient handling is becoming more popular trend in recent years bringing
new challenges to explore new avenues. Data analytics can be done more effi ciently with the availability of
distributed architecture of “Not Only SQL” NoSQL databases.
NOSQL Database Engines for Big Data Managementijtsrd
We are living in the digital world and last two decades have seen significant expansion in the information on internet technology. In present digital world the IOT is most popular term means computers, mobile phones and physical devices like sensors are connected to internet. With the rapid outreach of internet it is very important to focus on technological advancements for managing huge amount of data with easy access. Mrs. Yasmeen "NOSQL Database Engines for Big Data Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18608.pdf
Synopsis: Modern enterprises anticipate business requirements and work proactively to optimise the outcomes. If they don’t renovate or reinvent their data architectures, they lose customers, and market share. So my talk will be in detailing the importance of data architecture, architectural challenges if is not addressed and a case study - the learnings and success story by fixing the issues at the root - at the data storage & access.
Target Audience: Principal Software engineers & Architects
Key Takeaways: Importance of Modern Data Architecture, PostgreSQL & JSONB
I have given a talk @ https://hasgeek.com/rootconf/elasticsearch-users-meetup-hyderabad/
Data Ninja Webinar Series: Realizing the Promise of Data LakesDenodo
Watch the full webinar: Data Ninja Webinar Series by Denodo: https://goo.gl/QDVCjV
The expanding volume and variety of data originating from sources that are both internal and external to the enterprise are challenging businesses in harnessing their big data for actionable insights. In their attempts to overcome big data challenges, organizations are exploring data lakes as consolidated repositories of massive volumes of raw, detailed data of various types and formats. But creating a physical data lake presents its own hurdles.
Attend this session to learn how to effectively manage data lakes for improved agility in data access and enhanced governance.
This is session 5 of the Data Ninja Webinar Series organized by Denodo. If you want to learn more about some of the solutions enabled by data virtualization, click here to watch the entire series: https://goo.gl/8XFd1O
This white paper will present the opportunities laid down by
data lake and advanced analytics, as well as, the challenges
in integrating, mining and analyzing the data collected from
these sources. It goes over the important characteristics of
the data lake architecture and Data and Analytics as a
Service (DAaaS) model. It also delves into the features of a
successful data lake and its optimal designing. It goes over
data, applications, and analytics that are strung together to
speed-up the insight brewing process for industry’s
improvements with the help of a powerful architecture for
mining and analyzing unstructured data – data lake.
In this document, we will present a very brief introduction to BigData (what is BigData?), Hadoop (how does Hadoop fits the picture?) and Cloudera Hadoop (what is the difference between Cloudera Hadoop and regular Hadoop?).
Please note that this document is for Hadoop beginners looking for a place to start.
Exploring OrientDB as Graph Database model as NoSQL database.
The main goal of this project is to provide theoretical, technical details and debates on some powerful features of OrientDB. We provide some comparison attempts between OrientDB 2.1.8 and SQL Server 2012, they are mostly focused on MovieLens dataset and build recommendation engine.
An overview of Hadoop and Data warehouse from technologies and business viewpoints. The presentation also includes some of my personal observations and suggestions for people who want to join the field Big Data.
Data Integration Alternatives: When to use Data Virtualization, ETL, and ESBDenodo
Data integration is paramount, in this presentation you will find three different paradigms: using client-side tools, creating traditional data warehouses and the data virtualization solution - the logical data warehouse, comparing each other and positioning data virtualization as an integral part of any future-proof IT infrastructure.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/1q94Ka.
No sql databases new millennium database for big data, big users, cloud compu...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Presentation at Data Summit 2015 in NYC.
Elliott Cordo shared real-world insights across a range of topics, including the evolving best practices for building a data warehouse on Hadoop that also coexists with multiple processing frameworks and additional non-Hadoop storage platforms, the place for massively parallel-processing and relational databases in analytic architectures, and the ways in which the cloud offers the ability to quickly and cost-effectively establish a scalable platform for your Big Data warehouse.
For more information, visit www.casertaconcepts.com
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
View this webinar presentation as CenturyLink Technology Solutions (Formerly Savvis) and MapR as we deconstruct and demystify “the enterprise big data stack.” We provide you with a more holistic view of the landscape, explore use cases to show how you can derive business value from it, and share best practices for navigating through the fragmented big data environment.
Data Lake Acceleration vs. Data Virtualization - What’s the difference?Denodo
Watch full webinar here: https://bit.ly/3hgOSwm
Data Lake technologies have been in constant evolution in recent years, with each iteration primising to fix what previous ones failed to accomplish. Several data lake engines are hitting the market with better ingestion, governance, and acceleration capabilities that aim to create the ultimate data repository. But isn't that the promise of a logical architecture with data virtualization too? So, what’s the difference between the two technologies? Are they friends or foes? This session will explore the details.
This document covers guidelines around achieving multitenancy in a data lake environment. It mentions the different design and implementation guidelines necessary for on premise as well as cloud-based multitenant data lake, and highlights the reference architecture for both these deployment options.
Building a Logical Data Fabric using Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3FF1ubd
In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.
In this session, you will learn how your organization can apply a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization can reduce time to value. Hence, increasing the overall business value of your data assets.
KEY TAKEAWAYS:
- How a Logical Data Fabric is the right approach to assist organizations to unify their data.
- The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
- How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.
Data Ninja Webinar Series: Realizing the Promise of Data LakesDenodo
Watch the full webinar: Data Ninja Webinar Series by Denodo: https://goo.gl/QDVCjV
The expanding volume and variety of data originating from sources that are both internal and external to the enterprise are challenging businesses in harnessing their big data for actionable insights. In their attempts to overcome big data challenges, organizations are exploring data lakes as consolidated repositories of massive volumes of raw, detailed data of various types and formats. But creating a physical data lake presents its own hurdles.
Attend this session to learn how to effectively manage data lakes for improved agility in data access and enhanced governance.
This is session 5 of the Data Ninja Webinar Series organized by Denodo. If you want to learn more about some of the solutions enabled by data virtualization, click here to watch the entire series: https://goo.gl/8XFd1O
This white paper will present the opportunities laid down by
data lake and advanced analytics, as well as, the challenges
in integrating, mining and analyzing the data collected from
these sources. It goes over the important characteristics of
the data lake architecture and Data and Analytics as a
Service (DAaaS) model. It also delves into the features of a
successful data lake and its optimal designing. It goes over
data, applications, and analytics that are strung together to
speed-up the insight brewing process for industry’s
improvements with the help of a powerful architecture for
mining and analyzing unstructured data – data lake.
In this document, we will present a very brief introduction to BigData (what is BigData?), Hadoop (how does Hadoop fits the picture?) and Cloudera Hadoop (what is the difference between Cloudera Hadoop and regular Hadoop?).
Please note that this document is for Hadoop beginners looking for a place to start.
Exploring OrientDB as Graph Database model as NoSQL database.
The main goal of this project is to provide theoretical, technical details and debates on some powerful features of OrientDB. We provide some comparison attempts between OrientDB 2.1.8 and SQL Server 2012, they are mostly focused on MovieLens dataset and build recommendation engine.
An overview of Hadoop and Data warehouse from technologies and business viewpoints. The presentation also includes some of my personal observations and suggestions for people who want to join the field Big Data.
Data Integration Alternatives: When to use Data Virtualization, ETL, and ESBDenodo
Data integration is paramount, in this presentation you will find three different paradigms: using client-side tools, creating traditional data warehouses and the data virtualization solution - the logical data warehouse, comparing each other and positioning data virtualization as an integral part of any future-proof IT infrastructure.
This presentation is part of the Fast Data Strategy Conference, and you can watch the video here goo.gl/1q94Ka.
No sql databases new millennium database for big data, big users, cloud compu...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Data Lakehouse, Data Mesh, and Data Fabric (r2)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a modern data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. They all may sound great in theory, but I'll dig into the concerns you need to be aware of before taking the plunge. I’ll also include use cases so you can see what approach will work best for your big data needs. And I'll discuss Microsoft version of the data mesh.
Presentation at Data Summit 2015 in NYC.
Elliott Cordo shared real-world insights across a range of topics, including the evolving best practices for building a data warehouse on Hadoop that also coexists with multiple processing frameworks and additional non-Hadoop storage platforms, the place for massively parallel-processing and relational databases in analytic architectures, and the ways in which the cloud offers the ability to quickly and cost-effectively establish a scalable platform for your Big Data warehouse.
For more information, visit www.casertaconcepts.com
Fast and Furious: From POC to an Enterprise Big Data Stack in 2014MapR Technologies
View this webinar presentation as CenturyLink Technology Solutions (Formerly Savvis) and MapR as we deconstruct and demystify “the enterprise big data stack.” We provide you with a more holistic view of the landscape, explore use cases to show how you can derive business value from it, and share best practices for navigating through the fragmented big data environment.
Data Lake Acceleration vs. Data Virtualization - What’s the difference?Denodo
Watch full webinar here: https://bit.ly/3hgOSwm
Data Lake technologies have been in constant evolution in recent years, with each iteration primising to fix what previous ones failed to accomplish. Several data lake engines are hitting the market with better ingestion, governance, and acceleration capabilities that aim to create the ultimate data repository. But isn't that the promise of a logical architecture with data virtualization too? So, what’s the difference between the two technologies? Are they friends or foes? This session will explore the details.
This document covers guidelines around achieving multitenancy in a data lake environment. It mentions the different design and implementation guidelines necessary for on premise as well as cloud-based multitenant data lake, and highlights the reference architecture for both these deployment options.
Building a Logical Data Fabric using Data Virtualization (ASEAN)Denodo
Watch full webinar here: https://bit.ly/3FF1ubd
In the recent Building the Unified Data Warehouse and Data Lake report by leading industry analysts TDWI, we have discovered 64% of organizations stated the objective for a unified Data Warehouse and Data Lakes is to get more business value and 84% of organizations polled felt that a unified approach to Data Warehouses and Data Lakes was either extremely or moderately important.
In this session, you will learn how your organization can apply a logical data fabric and the associated technologies of machine learning, artificial intelligence, and data virtualization can reduce time to value. Hence, increasing the overall business value of your data assets.
KEY TAKEAWAYS:
- How a Logical Data Fabric is the right approach to assist organizations to unify their data.
- The advanced features of a Logical Data Fabric that assist with the democratization of data, providing an agile and governed approach to business analytics and data science.
- How a Logical Data Fabric with Data Virtualization enhances your legacy data integration landscape to simplify data access and encourage self-service.
What Are The Best Databases for Web Applications In 2023.pdfLaura Miller
A database is used to store and manage structured & unstructured data in a system. Read the blog to know 2023's top seven databases for web applications.
Development of a Web based Shopping Cart using the Mongo DB Database for Huma...AI Publications
The databases in use today are of SQL-type. This has its drawbacks such as unnecessary complex queries, rigid schema, non-asynchronous persistence and they are definitely not object oriented. Moreover, SQL-shopping cart is expensive by requiring more programs to function. Therefore, the development of a modern shopping cart using MongoDB will eradicate these set backs. The main aim of this study is to design and execute a modern e-commerce shopping cart using MongoDB database. The method used here is the agile development methodology. Stages involved here include: Brainstorm, Design, development stage, Quality Assurance, deployment and Cycle. The User interface is written with HTML, CSS and JavaScript. The HTML (Hyper Text markup language) is used to create the web pages involved, including the forms through which the user supplies input to the system. Each item in the web page is well labeled to optimize user friendliness. The CSS (cascading Style Sheet) is used to create a mobile-friendly, responsive interface to enable mobile devices to seamlessly use the system.The developed shopping cart will save time and effort for programmers rather than using SQL tools with all the labors with it.
Quantitative Performance Evaluation of Cloud-Based MySQL (Relational) Vs. Mon...Darshan Gorasiya
To compare the performance of MySQL (Consistency & Availability - CA) with MongoDB (consistency & partition - CP). Yahoo! Cloud Serving Benchmark (YCSB) automated workloads used for quantitative comparison with large and small data volume.
Analysis and evaluation of riak kv cluster environment using basho benchStevenChike
Many institutions and companies with technological development have been producing large size of structured and unstructured data. Therefore, we need special databases to deal with these data and thus emerged NoSQL databases. They are widely used in the cloud databases and the distributed systems. In the era of big data, those databases provide a scalable high availability solution. So we need new architectures to try to meet the need to store more and more different kinds of different data. In order to arrive at a good structure of large and diverse data, this structure must be tested and analyzed in depth with the use of different benchmark tools. In this paper, we experiment the Riak key-value database to measure their performance in terms of throughput and latency, where huge amounts of data are stored and retrieved in different sizes in a distributed database environment. Throughput and latency of the NoSQL database over different types of experiments and different sizes of data are compared and then results were discussed.
Analysis and evaluation of riak kv cluster environment using basho benchStevenChike
Many institutions and companies with technological development have been producing large size of structured and unstructured data. Therefore, we need special databases to deal with these data and thus emerged NoSQL databases. They are widely used in the cloud databases and the distributed systems. In the era of big data, those databases provide a scalable high availability solution. So we need new architectures to try to meet the need to store more and more different kinds of different data. In order to arrive at a good structure of large and diverse data, this structure must be tested and analyzed in depth with the use of different benchmark tools. In this paper, we experiment the Riak key-value database to measure their performance in terms of throughput and latency, where huge amounts of data are stored and retrieved in different sizes in a distributed database environment. Throughput and latency of the NoSQL database over different types of experiments and different sizes of data are compared and then results were discussed.
Effect of Type of School Management and School
Factors on Educational Performance of Primary
School Children in Navi Mumbai: Multiple
Classification Model
Rita Abbi
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Water billing management system project report.pdfKamal Acharya
Our project entitled “Water Billing Management System” aims is to generate Water bill with all the charges and penalty. Manual system that is employed is extremely laborious and quite inadequate. It only makes the process more difficult and hard.
The aim of our project is to develop a system that is meant to partially computerize the work performed in the Water Board like generating monthly Water bill, record of consuming unit of water, store record of the customer and previous unpaid record.
We used HTML/PHP as front end and MYSQL as back end for developing our project. HTML is primarily a visual design environment. We can create a android application by designing the form and that make up the user interface. Adding android application code to the form and the objects such as buttons and text boxes on them and adding any required support code in additional modular.
MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software. It is a stable ,reliable and the powerful solution with the advanced features and advantages which are as follows: Data Security.MySQL is free open source database that facilitates the effective management of the databases by connecting them to the software.
Water billing management system project report.pdf
Ijaprr vol1-2-6-9naseer
1. International Journal of Allied Practice, Research and Review
Website: www.ijaprr.com (ISSN 2350-1294)
NOSQL for Interactive Applications
Naseer Ganiee1
,Dr. Ruchira Bhargava2
Director,RationalTabsTechnologies, India
Department of Information Technology & Communication, India
1
naseer@rationaltabs.com;2
dr_ruchira@yahoo.in
Abstract— The scalability and high performance are the key aspects for interactive applications. The traditional
databases are not providing the necessary scalability and performance. NOSQL databases are the best choice for
applications that need to read and write huge amount of data swiftly. For best output it is mandatory to pick
scalable, fast and robust database.
Keywords— NOSQL; RDBMS; Big Data; Big Users; Auto-Shading; ACID; BASE
I. INTRODUCTION
Data management is the key for success of any organization and enterprises use a special
methodology for data management operations known as database management system which
provides ways of storing and accessing data efficiently with the help of databases. DBMS helps
industries to develop databases of their own choice for data management with the help of
different models proposed by experts that specifies the organization of data within a database.
From years we are using various data models for data management and the relational model is
the most successful and adoptable by professionals. The relational model is highly efficient in
terms of client server computing and very strong technology for storing structured data. In
present era several database models are available for data management like network model,
hierarchical model, object-oriented model, associative model, relational model and non-
relational model but it is mandatory to choose an appropriate one. Relational databases supports
all the essential characteristics of data management like simplicity, flexibility, compatibility and
scalability but fails to provide options like handling huge volumes of unstructured data when
implemented in cloud environment. The cloud computing is the modern type of computing that
enables us to use resources like applications, infrastructure etc. on the basis of pay-as-you-go
model. Most of the applications are database driven and strong database knowledge is required
for efficient data management.
II. NOSQLAND BIG DATA
The internet is a familiar technology used across the globe and big data is a real challenge in
present era. The organizations like facebook, google, amazon etc are also facing the big data
problem. To overcome the big data issue experts proposed a new system of data management
commonly known as NOSQL to meet the data management demands of present era. NOSQL
databases are different from traditional ones like not using the famous SQL query language, no
join operations and BASE support instead of ACID that is the core concept of relational
databases. The internet produces huge amount of data and huge amount of storage is needed to
IJAPRR Page 1
2. handle such data that is one of the dazzling feature of NOSQL. Not only handling system of
record applications NOSQL is also an analytic and business intelligence system that is very
important for the enterprise future, due to this reason most organizations have already espouse
NOSQL databases. Migrating to NOSQL approach is also proficient for software based
enterprises because reduced development time due to its simple data access terminology as
compared to traditional database management systems.
NOSQL databases are efficient for developers also because sometimes they are not able to
develop and test applications at locations other than offices due to lacking database resources.
On the other hand NOSQL databases are efficient for cloud environment offers on demand
resources, The NOSQL databases are efficient for small and medium enterprises because of
database as a service can be deployed on affordable costs as compared to oracle or MS SQL
Server that are costly. Due to easy deployment in cloud environment, NOSQL databases can be
used to store data for backup processes also and provide automatic online backups of changed
data in data centers.
No schema is required for NOSQL databases means data can be inserted in databases without
any schema defined and the format of inserted data is changeable at any time. Auto-Sharding or
elasticity is another aspect to shift towards NOSQL database approach because these databases
automatically spread data across multiple servers without requiring applications assistance and
the interesting thing is servers can be added or removed dynamically from the data layer. The
NOSQL ensure high availability because with replication can store multiple copies of data in a
cluster and is strong tool for disaster recovery. Partitioning in previous models can reduce the
power to perform complex queries but NOSQL databases retain full query significant power
even when distributed across thousands of servers.
There are three mega concepts that really obsessed the adoption of NOSQL technology Big
Data, Big Users and the latest IT computing the cloud computing. Today most of the
applications are hosted on cloud where they support global users 24 hours and more than 2
billion users are connected to the internet across the globe thus creating concurrent users in a
great quantity. Huge volumes of data is generated through different applications like personal
user information, user generated content, machine logging data, sensor generated data etc. for
managing such data efficiently experts want a flexible data management that easily
accommodates any new type of data they want to work with. NOSQL data model provides best
to the applications organization of data and simplifies the interaction between the application
and the database. Today most of the applications both consumers based and business based run
in a cloud and support large no of users. Cloud is based on 3-tier application architecture and in
this architecture application is accessed through a web browser or a mobile app and contains a
load balancer that moves the incoming traffic to the application servers for processing. It is
estimated for every 10,000 new concurrent users a new commodity server is added to the
application tier for load balancing. Using relational databases at databases tier that was
originally popular are now problematic because they are centralized and made them poor to
support applications that require dynamic scalability on the other hand NOSQL technology is
based on distributed concept and scale-out.
III.KEY DATABASE CRITERA FOR INTERACTIVE APPLICATIONS
There are some important factors to keep in mind when choosing a database for interactive
applications:
.
A. Scalability.
IJAPRR Page 2
3. When website traffic increase suddenly and database is not responding because not having
enough capacity, we need to scale database swiftly and without any changes in application. Also
having possibility to decrease and optimize the resources when system is at rest. Database
scaling needs to be very simple operation like not dealing with complicated database concepts or
any change in application.
B. Performance.
For better performance the database needs to support low latencies regardless of the data size and
load. The read and write latency of NOSQL databases is very low because of sharing of data
across nodes in clusters that is also the demand of interactive applications.
C. Availability.
Availability is one of the immense feature required in modern applications. For high availability
system should be able to support online upgrades, for maintenance it is very easy to remove a node
without affecting the whole cluster and provide options for backups and disaster recovery in case
the whole data center goes down.
E. Architecture.
Traditional databases are based on rigid schema and for any change in application we need to
change database schema as well on the other side NOSQL databases support flexible schema and
very simple query language.
IV.CONCLUSION
The database concept is very popular in application development. In present era of computing
we need to deploy optimized databases for application development. The paper describes the key
database features required for interactive applications. NOSQL databases are grooming day by day
because of the features required for enterprises to tackle the problems observed in traditional
databases.
V. ACKNOWLEDGMENT
I wish to acknowledge all the people who have worked in NOSQL Technology and whose work
inspired me to do research in NOSQL Technology and whose documents gave me the path to write
this research paper and developing my ideas for making the technology even better. I also would
like to acknowledge my partner Miss Ruchira Barghava and my colleagues at RationalTabs
Technologies Pvt. Ltd. who supported me to write one more research paper and put my ideas and
research on paper as a contribution to coming generation.
Special wishes to Couchbase and other contributors for developing NOSQL based products.
VI.REFERENCES
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[8] DataStax Corporation “NOSQL in the Enterprise”, 2011
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