Amazon RDS

During the migration from MySQL installed on Linux to AWS RDS, we were almost surprised as it was done by few clicks rather than too much configurations ans steps in case of traditional DB migrations. In no time our platform was up and running.

AWS RDS provides multiple Engines as compared to Google SQL AWS RDS provides more than 5 read replicas which a Google SQL does not AWS RDS is a cheaper option than Redshift for smaller datasets. Redshift is a Dataware house and must be used for super large datasets only Super easy configuration and Mangement for AWS RDS.

Because we have our whole architecure on AWS cloud so to provide close connectivity we have choose AWS RDS and also due to Features offered by AWS RDS.

The AWS relational database service was selected because at the early stages of the implementation of the company product the team didn't have a lot of experience in creating and configuring database inside the company cluster, but there was a need to have a relation database, and since other services from amazon where already been used, it sound wise to explore the RDS.

Amazon Relational Database Service solves part of our architecture problem - more inclined towards on-line transactions and simple user data storage - whereas MongoDB is good for storing structured complex data. For most of the requirements we use Amazon Relational Database Service for, it is because it is simpler and more straightforward to use, reducing the time for the development team to learn, and it also gives a slow latency and good performance.

Amazon Relational Database Service (RDS) stands out among similar products due to its seamless integration with other AWS services, automated backups, and multi-AZ deployments for high availability. Its support for various database engines, such as MySQL, PostgreSQL, and Oracle, provides flexibility. Additionally, RDS offers managed security features, including encryption and IAM integration, enhancing data protection. The pay-as-you-go pricing model makes it cost-effective. Overall, Amazon RDS excels in ease of use, scalability, and a comprehensive feature set, making it a top choice for organizations seeking a reliable and scalable managed relational database service in the cloud.

In a few words, we are just to confortable working with oracle and sql server. Using RDS add another layer of distributed database in order to backup everything we have in case of a disaster and also complies with authorities locally and internacionally. All database we use, are local in custom servers that we maintain, but we agree to expand this.

Deploying PostgreSQL by yourself may appear easy at first but running a production PostgreSQL cluster with millions of records is a hard task, especially for compliance, scalability, and security. RDS automates all complex tasks so you can focus on building your database schema and application.

With the latest serverless technology Amazon Relational Database Service (RDS) has an edge over all its competitors, it works really fast with high log retention.

RDS Provides broader range of database engine. Well integration capabilities with third party makes it unique

With products like Google Cloud SQL, Azure SQL Database, AWS RDS stacks up quite well in all features. Features like licensing, performance, security comes to my mind the most. Another aspect is AWS's global reach.

There are a lot of factor we took into consideration the most important ones are: Ease of use and setup - Compared to other similar options Amazon RDS is very easy to setup just clicking few options and its ready for POC and for production very easy and flexible Terraform code. Managed service - Amazon RDS greatly reduces the operational burden by taking care of the scalability, High availability and automated backups.

Hardware difference compared with Normal Database on physical servers

Amazon RDS supports a wider range of database engines, including MySQL, PostgreSQL, Oracle, Microsoft SQL Server, and Amazon Aurora (MySQL and PostgreSQL-compatible) than Google Cloud SQL. When compared to Google Cloud SQL, AWS provides a larger global footprint with additional availability zones and regions, potentially providing greater geographical redundancy and availability choices.

MongoDB is nosql database and some clients prefer it. In our presentation we try to persuade them to use RDS with its pros and cons. The type of selection depends upon the actual need.

Although the Rackspace service is not comparable, even though it is very good, it requires a lot of administration on my part.
Regarding Atlas, although it is not the same as RDS in terms of provisioning and administration panel, I mention it because I found it simpler and more accessible than RDS.

Previously used Media Temple database hosting (now GoDaddy). While that endeavor was also successful, the AWS RDS is more secure, with higher availability and better documentation.

We have a strong preference for AWS managed services, and we find that RDS offers excellent integration with various AWS services, making it a seamless choice for our infrastructure. Furthermore, RDS supports integration with automation tools such as Terraform, enhancing our operational efficiency. Additionally, RDS proves to be cost-effective for our organization.

The main area that stuck out to me in looking at AWS RDS compared to Azure Data Lake Storage was still that RDS is simple to get up and running with over its competitors. The only negative and it holds true for both solutions is that can both be hard to estimate cost control at the beginning.

RDS seems to be the best cross-section between cost, availability, deployment and throughput.

Also ElephantSQL. Not as cost effective, but more integrated into our cloud environment.

Installing, configuring, and managing Oracle Database can be challenging, especially for people who are new to Oracle products. Longer learning curves and higher operational overhead can be caused by this complexity. Amazon Relational Database Service is easy to understand and easy to use.

We consider initially only to have the back up product. After analysing different products, we realize that we needed a more complete and robust product such as Amazon Relational Database Service (RDS). Then, the option to hire Amazon Relational Database Service (RDS) was somehow easier, when comparing against other amazon services and other providers products (such as google).