Amazon Database Services

Amazon database services provide a scalable, flexible, and high-performance solution for a wide range of applications and workloads. These services are fully managed, meaning that AWS handles the underlying infrastructure and administration tasks such as managing high availability and scalability. This allows users to focus on their data and applications. They also integrate with other AWS services, allowing for seamless integration with other parts of an AWS application stack.

In this chapter, we will cover the following Amazon database services:

Amazon cloud relational databases: Fully managed AWS relational databases that can be used for transactional applications, reporting and analytics, and content management, including Amazon Relational Database Service (RDS) for traditional databases such as MySQL, MariaDB, PostgreSQL, Oracle, SQL Server, and Amazon Aurora for a high-performing, MySQL and PostgreSQL-compatible database.

Amazon cloud NoSQL...

Database basics

A database is an organized collection of data that is stored and managed on a computer. It allows for efficient storage, retrieval, and management of data, which can be used for a wide range of applications, such as websites, mobile apps, financial systems, and more. A database consists of one or more tables that contain related data. Each table contains rows and columns, where the columns represent the attributes or fields of the data, and the rows represent the individual instances or records of the data. There are many different types of databases:

• Relational databases: These are the most common type of database, where structured data is organized in a tabular format with rows and columns. Data is organized into tables, and relationships between tables are established through keys.
• NoSQL databases: These databases are designed to handle unstructured or semi-structured data that cannot be easily organized into tables. Instead, they use document-based,...

Amazon RDS

RDS is a fully managed relational database service provided by Amazon in the cloud. With RDS, AWS provides a few popular relational database management systems as a service, including MySQL, PostgreSQL, Oracle, SQL Server, and MariaDB.

Amazon RDS is a managed service. There are different ways to create a database, such as MySQL, in the cloud. One is provisioning an EC2 instance and installing a database management system (DBMS) on the instance, and then creating databases, tables, and so on. This is an unmanaged approach since you will have to take care of all the administrative tasks such as database scaling, high availability, disaster recovery, and so on. Another is using cloud-managed services to provision a database where AWS will handle the mundane and time-consuming tasks such as hardware provisioning, software installation, backup and recovery, patching, scaling, and so on. Managed services allow users to focus on their applications and data without worrying about...

Amazon cloud NoSQL databases

DynamoDB is a fully managed NoSQL database service provided by Amazon in the cloud. It is a key-value and document database that can handle structured, semi-structured, and unstructured data, making it a versatile solution for a wide range of applications. It is also designed to be highly available, with automatic multi-AZ replication for built-in redundancy and durability.

DynamoDB can scale seamlessly with no downtime or disruption, allowing users to scale their databases up or down as needed, with pay-as-you-go pricing based on the amount of data stored and the number of requests made.

DynamoDB is designed for high performance with sub-millisecond latency for read and write operations, making it an ideal choice for real-time, low-latency applications. It is also highly secure, with support for encryption at rest and in transit, as well as fine-grained access control through AWS IAM. We will create a DynamoDB through AWS Cloudshell:

aws dynamodb...

Amazon ElastiCache

ElastiCache is a fully managed, in-memory data caching service provided by Amazon in the cloud. ElastiCache supports two popular in-memory data stores, Redis and Memcached, which can be used as caching layers for a wide range of applications, including web applications, mobile applications, and gaming applications.

ElastiCache provides automatic scaling and availability, with the ability to scale up or down based on the needs of the application. It also integrates with other AWS services, such as Amazon EC2, AWS Lambda, and Amazon RDS, for seamless integration with other parts of an AWS application stack. ElastiCache provides a range of features for managing and monitoring the caching environment, including automatic failover and automated backups.

ElastiCache also supports a range of use cases, including read-heavy workloads, session management, caching database queries, and real-time analytics. It also supports a range of data structures, including strings...

Amazon cloud data warehouse service

Amazon Redshift is a cloud-based data warehousing service that is designed to provide fast querying and analysis of large datasets. Redshift is a fully managed service where AWS handles the infrastructure and administration tasks, such as hardware provisioning, software installation, and backup and recovery, to allow users to focus on their data and analysis without worrying about the underlying infrastructure.

Redshift is based on a columnar storage format, which provides efficient storage and fast querying of large datasets. It can scale up or down as needed, with pay-as-you-go pricing based on the amount of data stored and the number of queries made. It also integrates with other AWS services, such as Amazon S3, Amazon EMR, and Amazon Kinesis, for seamless integration with other parts of an AWS application stack. Redshift supports standard SQL and BI tools such as Tableau, MicroStrategy, and Looker, allowing users to perform complex analytics...

Summary

In this chapter, we discussed Amazon cloud databases including RDS, Aurora, DynamoDB, ElastiCache, and Redshift. We provisioned simple database instances and showed how to connect them and use the services. With all the different data schemas, business use cases, and application requirements such as size, scale, performance, and cost, selecting the right database is a critical step. More details are included at https://aws.amazon.com/startups/start-building/how-to-choose-a-database/.

In the next chapter, we will further explore Amazon’s big data services.

Practice questions

Questions 1-10 are based on Figure 4.16:

Figure 4.16 – Cloud architect diagram

1. RDS1 is created in VPC1. How would you configure it to be accessible from your home laptop?
   1. Configure SG for RDS1 and NACL for subnet1/subnet2.
   2. Configure SG for RDS1.
   3. Configure NACL for VPC1.
   4. Configure SG for VPC1.
2. Which of the following is not true?
   1. EC2-18 can access RDS1 via VPC peering.
   2. EC2-2 can access RDS1 within VPC1.
   3. EC2-8 can access RDS1 via VPC peering.
   4. EC2-1 can access RDS1 within VPC1.
3. An engineer is developing a web server W1 on EC2-18. W1 needs to access Dynamodb1. What is your recommendation?
   1. Create an EC2 role R1 for Dynamodb1 access, assign R1 to EC2-18, and create an endpoint for Dynamodb1 in VPC3.
   2. Create an EC2 role R1 for Dynamodb1 access, and assign R1 to EC2-18.
   3. Create an endpoint for Dynamodb1 in VPC3.
   4. Create an EC2 role R1 for Dynamodb1 access, assign R1 to EC2-18, create an endpoint for Dynamodb1 in VPC1, and create peering...

Answers to the practice questions

1. A
2. A
3. A
4. D
5. A
6. A
7. A
8. A
9. D
10. A

Further reading

For further insights into what you’ve learned in this chapter, refer to the following links:

• https://aws.amazon.com/products/databases/
• https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html
• https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Introduction.html
• https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_GettingStartedAurora.html
• https://docs.aws.amazon.com/elasticache/