![THANK YOU
CS-A
BATCH 2
GROUP 3
Prasanna Bhalerao [35]
Yash Bhalerao [36]
Atharva Chawle [50]
Chirag Belani [51]
Kalyani Chopade [52]](https://image.slidesharecdn.com/dbmsppt21-230831191240-e49221e5/85/amazon-database-27-320.jpg)
amazon database
- 1. Amazon DATABASES CS-A BATCH 2 GROUP 3 Prof. Anil Kadu
- 2. • Introduction to Amazon's database • Objectives • Amazon web services • Scalability and availability • Data security and privacy • Literature Review • References Table of Content
- 3. COMPANY GROUP Introduction to Amazon Platform: •Amazon.com is one of the world's largest e- commerce platforms, serving tens of millions of customers globally. •The platform offers a wide range of products, from books and electronics to clothing and household items. •At Amazon, reliability, scalability, and performance are critical to ensure an exceptional shopping experience for customers.
- 4. COMPANY GROUP Introduction to Amazon Database: • Amazon Database Services Overview: Amazon offers database services for secure data storage and organization. • Similar to a digital storage system, it's used for managing various data types. • Secure Data Storage: Amazon offers secure digital storage for various data types, ensuring data confidentiality. • Scalable Solutions: Businesses can easily scale resources to manage growing data needs efficiently. • Cost-Effective: Pay-as-you-go pricing minimizes upfront costs, making it budget-friendly. • Global Accessibility: Data centers worldwide provide low- latency access, benefiting users globally.
- 5. • The objective of exploring the topic of Amazon databases is to understand their scalability, flexibility, and how they can effectively handle large volumes of data, enabling businesses to grow and adapt to changing demands. • Another objective is to recognize the high availability and durability provided by Amazon databases, ensuring that data is always accessible, protected, and can be reliably recovered in case of failures, thus ensuring the smooth operation and continuity of businesses. Objective
- 6. TWO TYPES OF DATABASES RELATIONAL DATABASES NON-RELATIONAL DATABASES
- 7. • A relational database organizes data into rows and columns, which collectively form a table. • Structured Data Management : Relational databases organize data into structured tables with rows and columns. • ACID Properties : Relational databases follow ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring data integrity and reliability. • Multi-User Support : They provide concurrent access for multiple users or applications, ensuring data consistency. • Scalability Challenges : Scaling relational databases can be complex, especially when dealing with large datasets or high traffic loads. • Use Cases : Relational databases are suitable for a wide range of applications, including e-commerce, content management systems, and financial systems. Relational Databases
- 8. Amazon Web Services Amazon Aurora Amazon RDS Amazon Redshift
- 9. Amazon Aurora • Amazon Aurora is a fully managed relational database service that combines the performance and availability of a traditional enterprise database with the simplicity and cost-effectiveness of a cloud database. • Amazon Aurora is based on MySQL and PostgreSQL, but it adds a number of features that make it more scalable, reliable, and secure. • Aurora Storage Layer is durable and scalable. • Aurora Storage Layer can store data for multiple Aurora DB clusters. • Aurora Replicas are identical copies of the database. • Aurora Replicas are spread across multiple availability zones. • When you write data to an Aurora DB cluster, it is written to all of the replicas. • This ensures that your data is always available, even if one of the replicas goes down.
- 10. Amazon RDS • Amazon Relational Database Service (Amazon RDS) is a fully managed relational database service that makes it easy to set up, operate, and scale a relational database in the cloud. • Amazon RDS provides a Number of Features that make it a good choice for businesses of all sizes. • High Availability: It ensures high availability through multi-Availability Zone deployments, reducing downtime risk. • Scalability: Amazon RDS allows easy vertical and horizontal scaling for accommodating growing workloads.
- 11. Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed to help you quickly and easily analyze large amounts of data using standard SQL. • Automatic scaling : Amazon Redshift can automatically scale up or down based on your workload, so you only pay for the resources that you use. • Point-in-time restore : You can restore your data to any point in time within the past 90 days, so you can easily recover from accidental data loss or corruption. • Data encryption : Your data is encrypted at rest and in transit, so you can be confident that your data is secure. • Integration with Amazon S3 : You can easily import data from Amazon S3 into Amazon Redshift, and you can also export data from Amazon Redshift to Amazon S3.
- 13. Feature Amazon Aurora Amazon RDS Amazon Redshift Database engines MySQL and PostgreSQL MySQL, PostgreSQL, Oracle, MariaDB, SQL Server PostgreSQL Data storage Shared storage layer Dedicated storage Dedicated storage Availability zones Multi-AZ deployment Single-AZ deployment Multi-AZ deployment Automatic scaling Automatic scaling Manual scaling Manual scaling Performance Up to 5 times the throughput of a traditional MySQL database Up to 30 times the throughput of a traditional MySQL database Up to 100 times the throughput of a traditional PostgreSQL database Cost-effectiveness Pay for the storage and compute resources that you use Pay for the storage and compute resources that you use Pay for the storage and compute resources that you use Security Encryption at rest and in transit Encryption at rest and in transit Encryption at rest and in transit Migration support Supports migration from MySQL and PostgreSQL databases Supports migration from MySQL, PostgreSQL, Oracle, MariaDB, and SQL Server databases Supports migration from PostgreSQL databases
- 14. • Also known as NoSQL Databases • Flexible Data Models : NoSQL databases support various data models, including document, key-value, column-family, and graph databases, providing flexibility for different data types and structures. • Schema-less : Unlike relational databases, NoSQL databases are typically schema-less, allowing developers to store data without a predefined schema. • Scalability : NoSQL databases are designed for horizontal scalability, making it easier to handle large volumes of data and high traffic loads. • High Availability : Many NoSQL databases offer built-in high availability and fault tolerance features, ensuring data accessibility even in the presence of hardware failures. • Use Cases : NoSQL databases are commonly used for applications like content management systems, social media platforms, real-time analytics, and sensor data storage. Non-Relational Databases
- 15. DynamoDB • Fully Managed NoSQL Database : Amazon DynamoDB is a fully managed NoSQL database service that offers seamless scalability, automatic backups, and high availability. It eliminates the operational overhead of database management. • Scalability at Any Scale : DynamoDB can effortlessly handle workloads that range from a few requests per second to millions of requests per second. Its auto-scaling feature adjusts capacity to match traffic patterns. • Low Latency and High Throughput : DynamoDB provides single-digit millisecond latency for read and write operations, making it suitable for real-time applications like gaming and IoT. It supports high-throughput workloads with ease. • Flexible Data Models : It supports both document and key-value data models, enabling developers to store and query data in a way that best fits their application requirements.
- 16. Classification on the Basis of Requirements
- 17. Requirement Best database service Relational database engine Amazon Aurora, Amazon RDS, Amazon Redshift Data warehouse engine Amazon Redshift Lots of storage space Amazon Aurora More moderate amount of storage space Amazon RDS Small amount of storage space Amazon Redshift High performance Amazon Aurora More moderate level of performance Amazon RDS Good level of performance on a budget Amazon Redshift Database service that can scale up and down as needed Amazon Aurora Database service with a predictable level of scalability Amazon RDS Database service that can scale up to very large sizes Amazon Redshift
- 18. Scalability • You can adjust the computing power and memory of your database system, with a maximum limit of 32 CPUs and 244 GiB of RAM. • For Amazon Aurora, the database storage can automatically grow as your data needs increase, up to a maximum of 64 TB. Alternatively, you can set a maximum size yourself. • MVSOL, MariaDB, Oracle, and PostgreSQL engines can scale up to 32 TB of storage, while SQL Server supports up to 16 TB. • You can create copies of your main database called replicas, which can handle high-volume read requests from applications.
- 19. Availability • Always Accessible: Amazon's databases are designed to be highly available. • They use a Multi-Availability Zone deployment, which means your data is automatically replicated across different locations. • Automatic Backups and Recovery: Amazon's databases regularly take backups of your data and transaction logs.
- 20. Data Security and Privacy • They have a number of physical, electronic, and procedural safeguards in place to protect customer data. • They use industry-leading encryption features to protect data in transit and at rest. • Customers have control over how their data is stored and who can access it. • Amazon does not access or use customer data without their permission, except as required to prevent fraud or abuse, or to comply with law.
- 21. AUTHORS RESEARCH PAPER NAME ABSTRACT A STUDY ON AWS ARCHITECTURE Prangya Prachi Samantaray Dr. Aswini Kumar Mohanty Dr.Arati Pradhan • In the current era, cloud computing has become integral, offering enhanced IT resource utilization and services. • This growth has led to increased adoption of cloud solutions, with a focus on inter-cloud communication and security. • This paper centers on the hybrid cloud concept, particularly in the context of Amazon Web Services (AWS), discussing its integration with on-premises infrastructure and addressing key issues. Millions of Tiny Databases Marc Brooker Tao Chen Fan Ping • In 2013, a project was initiated to build a database for Amazon EBS that required high availability and strong consistency. • Recognizing the constraints of the CAP theorem and distributed systems, the approach shifted to creating a distributed system with numerous databases. • Physalia, a transactional key-value store, was developed to provide high availability and strong consistency for cloud control systems. • It strategically places data based on transaction patterns and infrastructure knowledge. • This paper discusses its role in Amazon EBS and its broader applicability to distributed system challenges.
- 22. AUTHORS RESEARCH PAPER NAME ABSTRACT Database Security Management for Healthcare SaaS in the Amazon AWS Cloud Fabio Bracci, Antonio Corradi, Luca Foschini • The rise of healthcare Cloud computing as an evolution of networking, SaaS, and security best practices. • Describes how to make healthcare SaaS services compliant in the Cloud, ensuring data security standards are met. • Encryption & security key management functions can be easily added without compromising system performance. • Future work involves conducting experiments on larger-scale Cloud deployments and exploring different Cloud providers like OpenStack. Amazon Relational Database Service Delivers Enhanced Database Performance at Lower Total Cost Carl W. Olofson, Matthew Marden • Amazon RDS supports six database engines the open source MySQL, PostgreSQL, and Maria DB, as well as Oracle, Microsoft SQL Server, and Amazon’s own cloud-native RDBMS, Aurora. • They required databases that they could cost-effectively scale to match business demand in a cost-effective but high-performing manner. • It is a cloud-native database service aligned with cloud strategies,. IDC's study demonstrates the value of running various database workloads and engines in RDS.
- 23. AUTHORS RESEARCH PAPER NAME ABSTRACT Analysis of research on amazon AWS cloud computing seller data security Muhammad Talha, Mishal Sohail, Hajar Hajji • Big data and cloud computing are intertwined; major cloud companies like Google and Amazon handle vast amounts of big data. • There are two types of RDS databases: Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) Amazon uses AWS cloud computing to implement data analysis and mining, with a high level of security protection • Significance of this big data in the amazon dataset is beyond collection and aggregation. • Its true value emerges during processing, analysis, visualization, and application. Core big data concerns encompass data origin, analysis, and commercialization. Dynamo: Amazon’s Highly Available Key- value Store Avinash Lakshman, Alex Pilchin, Swaminathan Sivasubramanian • Amazon.com faces a massive-scale reliability challenge due to the global e-commerce operation's size. • This paper introduces Dynamo, a highly available key-value storage system. • Dynamo prioritizes availability over consistency and employs object versioning and application-assisted conflict resolution.
- 24. AUTHORS RESEARCH PAPER NAME ABSTRACT Using the Amazon Metric to Construct an Image Database based on what people do Robert Columb , Theodor G Wheld • The General approach of constructing an image database based on people's activities or behaviors, using methods is commonly employed in data analysis and computer vision. • Defining scope & objective Data collection • Data Annotation • Dimensionally Reduction • Data Construction Data Analysis • Improvement and Application A Feasible Schema Design Strategy for Amazon DynamoDB: A Nested Normal Form Approach Wai Yin Mok and the University of Alabama • Designing a schema for Amazon DynamoDB involves making decisions about the structure of your tables and the organization of your data to optimize performance, scalability, and cost- effectiveness. • First understand the DataModel ,Start with Entities, Denormalize it, Hierarchical Data Modelling identify the PK,CK and FK, batch operation and transaction ,estimate and optimize capacity units ,testing and optimization
- 25. AUTHORS RESEARCH PAPER NAME ABSTRACT Research Paper on AWS Cloud Infrastructure vs Traditional On-Premise Akshay Kushwaha • This paper highlights the advantages of AWS Cloud over on- premises solutions and introduces AWS services. • AWS, launched in 2006, has seen widespread adoption, with 77% of enterprises having cloud applications or infrastructure. • It offers a wide range of global cloud products with over one million active enterprise customers, featuring on-demand services and over 140 offerings. • This enables rapid response to changing business needs for startups, SMBs, and the public sector.
- 26. Questions ?
- 27. THANK YOU CS-A BATCH 2 GROUP 3 Prasanna Bhalerao [35] Yash Bhalerao [36] Atharva Chawle [50] Chirag Belani [51] Kalyani Chopade [52]