AWS Database Service

Introduction

Data is a significant resource for any modern firm. Information about clients, operations, commodities, and services is critical not only for day-to-day operations, but also for long-term survival and growth. Successful data storage, security, and retrieval may make all the difference when it comes to offering outstanding customer experiences, optimizing operations, and making informed, proactive decisions. Successful data storage, security, and retrieval may make all the difference in terms of providing exceptional customer experiences, optimizing operations, and making educated, proactive decisions(Narasimhan G, 2018). Given the importance of data and appropriate data management, data management decisions are crucial. Cloud computing users now have more database options than ever before, and Amazon Web Services (AWS) provides several of them(Mukherjee, 2019).

AWS has numerous databases to choose from, making it easier to locate one that meets the business requirements without sacrificing quality—as long as someone first grasp the benefits and drawbacks of each option(Soltys, 2021). When deciding on the ideal database for the project, it is recommended determining the degree of utility expected from the service and then selecting a service based on the capabilities it offers.

Types of Databases supported by AWS

1. Key-value databases – Key-value databases, often known as non-relational databases, store data via the fundamental key-value mechanism. Individual values within a collection are individually identified using key-value pairs, and each value is recorded as a key-value pair with its matching key(Choi et al., 2018). This works in the same way as a dictionary: the key is the term, and the value is the definition of the term.
2. In-memory databases – An in-memory database is a type of non-relational database that stores data in memory rather than on disk, allowing queries to perform faster(El-Zoghby & Azer, 2018).
3. Document databases – Document databases, whether for catalogs or user profiles, or for content management systems such as blogs or streaming video platforms, provide versatile, semi-structured, hierarchical storage for a wide range of applications(Pothecary, 2021b).
4. Graph databases – Graph databases, as opposed to traditional databases, store data in a web-like format that allows complicated relationships between data to be mapped and searched.
5. Time series databases – Using time-series databases, it is possible to store and retrieve data points that are linked together by timestamps(El-Zoghby & Azer, 2018).
6. Ledger databases – Data in ledger databases is organized in tables, and an immutable journal records all data changes, resulting in a blockchain-like record of all data changes(Narasimhan G, 2018).

Amazon Relational databases:

Tables with columns and rows are used to store data in relational databases, with each row representing a single record and each column containing data about that item. Each row contains a distinct identification known as a key. Since the 1970s, relational databases have been the most often utilized type of data warehouse(Narasimhan G, 2018). SQL is a computer language for relational database management systems.

Amazon RDS is the best way to set up and keep up with relational databases in the cloud. Amazon RDS is a cloud database service that lets cloud administrators set up, manage, and grow relational cloud database instances(Amazon RDS Data Service). This service is called Amazon RDS.

People who run Amazon RDS can use a variety of tools to do this, like the AWS Management Console, Amazon RDS API calls, and the AWS Command Line Interface(Amazon RDS Data Service). These APIs are used to make database instances that users can then change. There are a lot of different types of instances that one can choose from, each with a different set of resources. These resources include processor speed, RAM size, storage capacity, and networking options. Each type comes in a variety of sizes to meet the needs of different jobs(Amazon RDS Data Service). To make sure that only people who need access to an RDS database have it, users of AWS Identity and Access Management can set up permissions for the database.

Features of Amazon RDS:

RDS has three main types of storage: in general, solid state drives (SSD) can be used for a lot of different types of data. People who work for Amazon usually store their things in this way. Based on the number of input-output operations per second that can be done at the same time, SSD storage is best for applications that need a lot of I/O(Amazon RDS Data Service). it also uses Magnetic which is a cheaper choice.

Amazon CloudWatch is a service provided by Amazon that helps people keep an eye on data. It tells people how much space and how many times they can use it. Moreover, RDS provides patches that work with any database engine that a user chooses to work with(Amazon RDS Data Service).

RDS also provides backups and allows users to get back to a specific point in time with the help of managed backups that include transaction logs. For databases, users can choose how long they want them to be kept(Amazon RDS Data Service). They can then restore them to any point in time from that time period. In addition, they can take manual snapshots of instances, which will stay in place until the user stops them.

This is what Amazon RDS databases look like.

Amazon RDS instances and the resources they use can be set up, configured, managed, and shut down by a database administrator. An Amazon RDS instance is used to set up the cloud database environment(Amazon RDS Data Service). Administrators can also make a lot of different databases or schemas, depending on what kind of database they’re working with.

Each customer has a maximum of 40 database instances in their Amazon RDS account. There are more rules for AWS-hosted Oracle and SQL Server instances(Amazon RDS Data Service). Many databases have a limit on how many databases a person can use at once.

Amazon RDS database engine.

1. Amazon Aurora: This is a relational database engine that Amazon Web Services makes and gives away. Amazon Aurora can run the databases MySQL and PostgreSQL.
2. RDS for MariaDB: RDS for MariaDB is a branch of MySQL that works with MariaDB, which is an open source relational database management system (RDBMS) (Amazon RDS Data Service).
3. RDS for MySQL: RDS for MySQL is able to work with the open source relational database management system, MySQL(Amazon RDS Data Service).
4. RDS for Oracle Database: There are a lot of different Oracle Database editions that work with RDS for Oracle Database, like Oracle Database editions and a lot more(Amazon RDS Data Service).
5. It’s also compatible with the open source PostgreSQL object-RDBMS, so RDS for PostgreSQL is also good for that(Amazon RDS Data Service).
6. RDS for SQL Server is a relational database management system that works with Microsoft SQL Server (RDBMS(Amazon RDS Data Service)).

Amazon RDS keeps adding support for more and more major and minor database engine versions. The goal of a database instance is to let database managers choose which engine version to use when they start a new database(Mukherjee, 2019).

Amazon RDS applications:

1. Online retailing: The practice of internet-based retailing is the sale of things via the internet. These programs, which work on massive databases, keep track of inventories, transactions, and pricing(Mukherjee, 2019).
2. Mobile and online gaming: RDS for online and mobile gaming advantages both developers who must maintain their applications current and customers who demand high application availability(Mukherjee, 2019).
3. International travel applications. RDS’s ability to automate database replication assists applications like Airbnb by lowering the amount of time spent on time-consuming database administration chores(Amazon RDS Data Service). Additionally, mobile applications such as Airbnb make use of RDS’s scalable storage feature(Soltys, 2021).
4. Applications for streaming data. Amazon RDS’s storage scalability and availability, for example, enable Netflix to meet daily demand, allowing the firm to grow its operations(Pothecary, 2021).
5. Financial applications: Finance RDS applications may be employed by these apps, as well as other mobile applications, to streamline administrative database processes and save time and money on the back end(Amazon RDS Data Service).

Amazon Aurora

Amazon Aurora is a database engine that Amazon developed entirely on its own. It contains Amazon Aurora databases, which are Amazon RDS’s database engine and instance management solution. Amazon Aurora Serverless, which is available on the AWS Marketplace, can be used to manage Amazon Aurora instances(Amazon RDS Data Service). Developers no longer have to worry about manually launching servers or checking database capacity thanks to the automated functionalities(Pothecary, 2021). RDS requires manual server scaling, which may result in extended periods of downtime. Aurora Serverless autonomous scaling capabilities allows a speedier deployment with minimal to no downtime, resulting in a more cost-effective solution.

Businesses should carefully weigh the advantages and disadvantages of the two database management techniques. Aurora is a good choice for usecases that suffer unplanned large demand spikes and require more effective capacity adjustment(Narasimhan G, 2018). Because Amazon RDS capacity increases take longer than Aurora Serverless, it is better suited to applications that demand a greater degree of predictability(Narasimhan G, 2018).

Conclusion

Amazon RDS, a relational database management service, enables organizations to conduct activities such as migration, backup, recovery, and patching. Amazon RDS’s replication, high-performance storage, and failure detection capabilities set it apart from other cloud computing services. One of the most alluring features of Amazon RDS is its simplicity of use. Administration of many database instances is easier by the absence of the need for administrators to acquire additional database administration tools. RDS’s capabilities enable organizations to cut costs associated with time-consuming database administration procedures, as well as the hidden costs associated with accessing AWS’ high-performance storage. This article discusses how to keep AWS costs under control.

References

Choi, J., Lian, R., Li, Z., Canis, A., & Anderson, J. (2018). Accelerating memcached on AWS cloud FPGAs. ACM International Conference Proceeding Series. https://doi.org/10.1145/3241793.3241795

Data Types – Amazon RDS Data Service. (n.d.). Retrieved April 8, 2022, from https://docs.aws.amazon.com/rdsdataservice/latest/APIReference/API_Types.html

El-Zoghby, A. M., & Azer, M. A. (2018). Cloud computing privacy issues, challenges and solutions. Proceedings of ICCES 2017 12th International Conference on Computer Engineering and Systems, 2018–Janua(48), 154–160. https://doi.org/10.1109/ICCES.2017.8275295

Mukherjee, S. (2019). Benefits of AWS in Modern Cloud. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3415956

Narasimhan G, L. (2018). EAI Endorsed Transactions Database Migration on Premises to AWS RDS. 3(1), 1–7.

Pothecary, R. (2021a). Databases. Running Microsoft Workloads on AWS, 81–109. https://doi.org/10.1007/978-1-4842-6628-1_4

Pothecary, R. (2021b). Running Microsoft workloads on AWS : Active Directory, databases, development, and more.

Soltys, M. (2021). Cloudifying the Curriculum with AWS. Proceedings – Frontiers in Education Conference, FIE, 2021–Octob, 1–12. https://doi.org/10.1109/FIE49875.2021.9637242