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By: The FantasticFour: Md Ismail Sharfi Prasoon Kant Ojha Krishnandu Pramanik Mohammad Jamilish Shiyamul Hoda Mentor: Mr. Sk. Safikul Alam

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My presentation on my final year project.

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By: The FantasticFour:Md Ismail Sharfi

Prasoon Kant Ojha

Krishnandu Pramanik

Mohammad Jamilish Shiyamul Hoda

Mentor: Mr. Sk. Safikul Alam

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Cost of Hardware & Software.

Cost of Staff Training.

Appointing Technical Staff.

Database Damage

Inefficient use of hardware.

Limitations of Traditional DBMS

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Predictable any time, anywhere access to

resources

Lower hardware and energy costs

Lower total cost of operations both for software licensing and administration tools-only pay what you use

Provides a better( up to 100%) utilization of hardware resources.

Why Cloud?

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DBMS as a Cloud Service

Much more efficient in its duties.

Cheaper in long run.

Cloud-based DBMS are extremely scalable.

Move much of the operational burden of

provisioning, configuration, scaling, performance

tuning, backup, privacy, and access control from the

database user to the service operator.

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A Cloud Database Management System (CDBMS)

is a distributed database that delivers computing as aservice instead of a product. It is the sharing ofresources, software and information betweenmultiple devices over a network which is mostly theinternet.

An example of this is Software as a Service, or SaaS, which is an application that is delivered through the browser to customers.

CDBMS

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A DBaaS (database-as-a-service) promises to move much of the operational burden of provisioning, configuration, scaling, performance tuning, backup, privacy, and access control from the database user to the service operator offering lower overall cost to users.

Database as a Service for the Cloud

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Efficient multi-tenancy

Elastic scalability

Database privacy

We argue that these three challenges must be overcome before outsourcing database software and management becomes attractive to many users, and cost effective for service provider.

Challenges to Implement

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Cloud based DBMS services are provided in a

multitenancy environment with elastic resources allocation, for use in simple and complex transaction

Most of the currently available DBMS engines will run on cloud infrastructure, but are not specifically engineered to take advantage of cloud.

Why NextBase?(DBMS in Cloud)

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Why Cloud?

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Privacy

A Significant barrier to deploy database in the cloud is privacy.

If client able to encrypt all the data stored in the DBaaS then privacy concern would largely be eliminated.

CryptDB is a technique designed to provide privacy. this privacy even prevent admin from seeing users data.

Reduction in throughput by 22.5%.

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Architecture

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Above is proposed DBMS in Cloud Architecture, first layer isthe storage, followed by databases and the upper layer isapplication layer. in terms of performance ,it providesefficient data access with a better distribution of values forsome data. It stores data in memory, avoiding the need fortime-consuming recompilation at run time. Produces adetailed report on each step used for data access, allowingyou to accurately implement performance enhancements.Data is encrypted when stored or backed up, without anyneed for programming to encrypt or decrypt.

Architecture

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USER REQUIREMENTS

Simple API

High performance

High availability and reliability

Easy access to advanced features

PUBLIC CLOUD REQUIREMENTS

cheap ,predictable and proportional to actual usage

security and privacy guarantees

Requirements

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Provider Requirements

Meet user services level agreement

Limit hardware and power costs

Limit administration costs

Requirements

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Screen ShotsLogin / Signup

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Screen ShotsList of Tables

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Screen ShotsCreate new database

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Screen ShotsEnter password for your database

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Screen ShotsCreate New Table

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Screen ShotsEnter Values into your table

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Screen ShotsDelete row from table

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Screen ShotsLogout

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EJB Server Overview

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Complete SQL functionalities.

Security Features.

Cloud Based.

Multi User.

RDBaaS.

Future Works

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ACM /IEEE COMPUTER SOCIETY MEETING

Thursday, December 17 Bigtable: A Distributed Storage System for Structured Data, Fay

Chang, Jeffrey Dean, Sanjay Ghemawat, Google Inc. Dynamo: Amazon’s Highly Available Key-value Store,

Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, AvinashLakshman, Amazon.com.

AbadiD, “Data Management in the Cloud: Limitations and Opportunities”, Bulletin of the IEEE Computer Society Technical Committee on Data Engineering (2009).

H.Hacigumus, B.Iyer, S.Mehrotra, executing SQL over Encrypted database-service provider model, ACM SIGMOD, 2002

References

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