Amazon RDS

I think compared to RAC environments for Amazon Relational Database Service (RDS) works well in limited Hardware . good for small size dbs and applications . Storage usage and process of adding storage . In my opinion, not good for bigger applications. I think patching Needs improvements and is not best suitable in case of high available applications.

Amazon RDS is an ideal choice when you need rapid database deployment for your project due to its user-friendly configuration and robust automation support, including Terraform and CloudFormation. Being a managed service, AWS assumes responsibility for its management, ensuring reliability. However, it may not be the best fit if you require extensive control over your databases.

RDS only works if you have access to someone who really knows the product. Don't dabble with RDS - do the full cost-benefit and go all in, if it's what you conclude that you need, including an employee or contractor who has demonstrated rich experience in the product who will actively configure the full product, and deploy monitoring tools to call attention to log alerts, downtime, demand changes and/or cost increases.

With the rapid growth of product offerings and increasing customer demand, managing inventory efficiently has become a complex challenge for many businesses. Traditional self-hosted databases are often struggling to keep up with the scale and complexity of modern inventory management operations. Businesses face issues with data consistency, performance bottlenecks, and inventory tracking accuracy. where the AWS RDS comes into picture to minimise our problems such as scalability , High Availability , Data Integrity, and Security.

-No need to install on Server
-Easy to scale up and define config
-Easy to connect just passing the config url
-Easy to see the logs compared to any RDS logs in the server.

Well suited : If you are handling huge data and want to give high performance and also do scrubbing to the data based on the requirements

Less Approproiate : Machine Learning and R Services are not available in Amazon Relational Database Service (RDS), Limited support for Linked Servers

well suited to host a database, if used for shorter duration.
Most suited for customer who do not want to bother about underlying hardware maintenance or OS-patching

In most of the use cases where an RDBMS is required, RDS can easily be sufficient. It is easy to set up and manage. Works great specifically where there is no requirement for very granular control of the database, and does not have very high performace. Because RDS is not going to provide the level of granular control that you can have on self hosted DB as it is partially managed by AWS. And for high performance, RDS doesn't scale as good as products like Aurora. However, unless there are very specific requirements, RDS does the job most of the time.

Well-suited scenarios:-1. Web Applications - RDS is an excellent choice for web applications that rely on relational databases2.E-commerce Platforms- E-commerce websites often have rapidly changing data and require high availability. RDS is well suited for this. Less appropriate scenarios:- Non-relational Data: If your data doesn't have a structured, tabular format and doesn't require SQL queries, a NoSQL database like Amazon DynamoDB or AWS DocumentDB may be a better choice than RDS.

Amazon RDS is well suited for dealing with many different kinds of relational databases. This includes popular ones such as Oracle, PostgreSQL, and Microsoft SQL. RDS lets users at my company easily manage, configure, and backup instances when it fits the situation.it is less appropriate for logs. RDS does not provide a full set of logs when debugging.

It is suitable for database hosting where the data is not classified as sensitive and meet the requirements of company security policy. Even Relational Database Service (RDS) provide encryption for data at rest but it is still hosted on the cloud hence certain risk assessment must be made and risk mitigation measure must be applied.

Offers a secure way to implement a database cluster that can be adapted on every usage requirement, thanks to multiple engines you can choose everything you need.

It is a very good solution for web applications. RDS is scalable and has supported many databases so it can provide a database solution regardless of how many users you expect for your application and you can choose which database to use based on your application's needs. Works well for all environments (QA, PROD, etc.) and deployment can be automated with scripts so it will cause work only once.

Good for scaling your application in multiple regions, storage issue fix as with config it can grow, easy to set up from console or using AWS CLI.

Amazon Relational Database Service (RDS) is well suited where you need a managed database. It is also good using Aurora when you want a serverless version that is a bit faster and more managed by AWS. It is a good choice of a database due to the different flavours available like MariaDB, MySQL, Oracle DB, etc. It is good when you want features like automatic backups, automatic upgrades, auto-scaling, high availability, etc. It is a good choice for the production environment. It is not a good choice for those databases where you need more access on the system level or looking for deep access to logs or for a database that is not available on AWS RDS like AS400, etc.

RDS is well suited for application environments where the developers don't have time to worry about the database. If the application requires a DB that is "fire and forget," RDS can be a rock solid implementation. This is particularly true for teams that may not have DBA resources or don't have a team member with extensive database admin skills. With some basic understanding, teams can stand up a DB in RDS and move on to the task of developing and maintaining the applications that use the DB.

RDS may be less appropriate for high performance applications where every level of the systems needs to be finely tuned. On the one hand, a novice developer may be able to get the required performance by scaling up to a large instance size while a proficient DBA could get the same performance from a finely tuned database running on an EC2 instance where access to the OS is available.

Pricing might also be a factor against RDS for teams that have limited budgets. Again, higher performing DB instances might be priced slightly more than the same DB running on a stand-alone server.

If you're operating within the Amazon universe of cloud computing, it's almost a no-brainer to utilize [Amazon Relational Database Service (RDS)]. RDS is well suited for probably a majority of applications that are candidates to host on a cloud computing platform as it reduces overall management and complexity of your system.

However, if you're doing a lot of data exporting/importing using tools that write to/read from the disk on the server, you may have challenges integrating RDS, as you have no access to the underlying host.

Amazon Relational Database Service is well-suited if the project requires high factor time to market. It is a good approach to enable full-fledged services in a quick manner using IaC deployment methods.

If you have the rest of your infrastructure in AWS, it is easiest to use Relational Database Service for your databases rather than build out your own servers in EC2. The server maintenance, clusters, etc. are all done for you, and you have technical support you can call rather than having to troubleshoot everything yourself.
If you have non-Microsoft databases, you have the ability to set up read replicas so your database writes are not slowed down.

Amazon RDS is the best suitable solution if you want to store sensitive data in the cloud with high availability and scalability of the database. Cost is a major concern. If your organization is financially small, then only you have to search for another solution.

Great for anyone just getting started with hosted RDS, and looks to have the price advantage as well. Leveraging other AWS services are very helpful, so as not to have to learn different configurations/tools to adjust RDS vs EC2, etc.

RDS is outstanding for sensitive data, e.g. user credentials and PII, because you can get excellent encryption at rest and security features for relatively little expense. For simple data structures and relationships, I highly recommend RDS. For more complex and intricately interrelated structures, DynamoDB is probably a better offering, but its lack of at-rest encryption makes it inappropriate for credentials, PII, etc.

RDS also integrates extremely well with ElasticBeanstalk, Lambda, and so on, and has functionality to trigger and/or respond to events from other AWS services, such as SQS.

Using it for MySQL or postgresql is a no brainier. MS SQL and Oracle support may not be a fit depending on use case.

If you can host your stuff in the cloud, AWS RDS is probably the best go-to that I've worked with to date. It is flexible enough for most applications, includes enough SQL dialects (MySQL, Postgres, et al) to satisfy any engineer who wants to work with a relational database for general purposes. It's also useful for smaller data warehousing. For larger applications and analytics warehousing, use Redshift or similar. RDS will fail/be slow. There are better, specialty products for this.

If your application relies on legacy database engine features, you may not want to use Amazon Relational Database Service. If you are under regulatory (or business, for that matter) requirements to retain database backups for longer than 30 days, are you capable of writing a workaround? Are database dumps sufficient, or do you need file level backups?