Amazon Relational Database Service (Amazon RDS) is a database-as-a-service (DBaaS) from Amazon Web Services.
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AWS Lambda
Score 8.3 out of 10
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AWS Lambda is a serverless computing platform that lets users run code without provisioning or managing servers. With Lambda, users can run code for virtually any type of app or backend service—all with zero administration. It takes of requirements to run and scale code with high availability.
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Per 1 ms
Pricing
Amazon Relational Database Service (RDS)
AWS Lambda
Editions & Modules
Amazon RDS for PostgreSQL
$0.24 ($0.48)
per hour, R5 Large (R5 Extra Large)
Amazon RDS for MariaDB
$0.25 ($0.50)
per hour, R5 Large (R5 Extra Large)
Amazon RDS for MySQL
$0.29 ($0.58)
per hour, R5 Large (R5 Extra Large)
Amazon RDS for Oracle
$0.482 ($0.964)
per hour, R5 Large (R5 Extra Large)
Amazon RDS for SQL Server
$1.02 ($1.52)
per hour, R5 Large (R5 Extra Large)
128 MB
$0.0000000021
Per 1 ms
1024 MB
$0.0000000167
Per 1 ms
10240 MB
$0.0000001667
Per 1 ms
Offerings
Pricing Offerings
Amazon RDS
AWS Lambda
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Amazon Relational Database Service (RDS)
AWS Lambda
Considered Both Products
Amazon RDS
Verified User
Engineer
Chose Amazon Relational Database Service (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.
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 …
Amazon RDS is more resilient and accepted industry wide when compared to its peers. Also, as we have other services on AWS so it would be easier to integrate with other services like ECS if we go with Amazon RDS. Furthermore, it would be more cost effective if we go with Amazon …
It is more suitable for our data structure and also has a lower management and implementation cost since we don`t have to do everything from scratch. It also offers great integration with other AWS services which makes it really good to work with.
I've used on-site MSSQL, Oracle, and IBM DB2 as well as MSSQL and postgresql in Azure, and RDS is much easier to setup than any of those aforementioned engines/setups. This includes initial setup, maintenance, security, and configurations. RDS also makes it easy to get …
We used to have On-Premises servers with Microsoft SQL Server and MySQL databases. We used that for years, and we had a hard time and a lot of work involved in securing and updating the server. And not no mention that growth involves a lot of calculations and extra costs. …
In this response, I'm specifically comparing RDS to running a database on an EC2 server. With EC2, the team owns all of the administrative and operational responsibilities. Patching the operating system patching and database software become another task that developers or …
Actually you can have most of these tools through AWS Relational Database Service as they are basically those technologies provided as a service. It is way better to have those products provided as a service through a huge and reliable infrastructure like AWS.
Our other application components are all hosted within Amazon's systems already, and the tight coupling of RDS with the security groups and virtual private cloud offerings made locking down privacy and security much easier than integrating with an outside provider. The deeper …
Initially, we planned to move everything to Dynamo DB, however, we had our initial architecture with MySQL, so we thought it would be a good option to migrate and use AWS RDS which seemed to be a good idea actually. I feel the security and the placing it in a VPC, is one …
When we use Lambda, we do not need to worry about the infrastructure and costs. AWS can handle it all on its own. For an optimum use case, one can always use AWS Lambda along with API Gateway and Route 53 for the best use case. Cloudwatch can help you identify any issues and …
If your application needs a relational data store and uses other AWS services, AWS RDS is a no-brainer. It offers all the traditional database features, makes it a snap to set up, creates cross-region replication, has advanced security, built-in monitoring, and much more at a very good price. You can also set up streaming to a data lake using various other AWS services on your RDS.
Lambda excels at event-driven, short-lived tasks, such as processing files or building simple APIs. However, it's less ideal for long-running, computationally intensive, or applications that rely on carrying the state between jobs. Cold starts and constant load can easily balloon the costs.
Automated Database Management: We use it for streamlining routine tasks like software patching and database backups.
Scalability on Demand: we use it to handle traffic spikes, scaling both vertically and horizontally.
Database Engine Compatibility: It works amazingly with multiple database engines used by different departments within our organization including MySQL, PostgreSQL, SQL Server, and Oracle.
Monitoring: It covers our extensive monitoring and logging, and also has great compatibility with Amazon CloudWatch
It is a little difficult to configure and connect to an RDS instance. The integration with ECS can be made more seamless.
Exploring features within RDS is not very easy and intuitive. Either a human friendly documentation should be added or the User Interface be made intuitive so that people can explore and find features on their own.
There should be tools to analyze cost and minimize it according to the usage.
Developing test cases for Lambda functions can be difficult. For functions that require some sort of input it can be tough to develop the proper payload and event for a test.
For the uninitiated, deploying functions with Infrastructure as Code tools can be a challenging undertaking.
Logging the output of a function feels disjointed from running the function in the console. A tighter integration with operational logging would be appreciated, perhaps being able to view function logs from the Lambda console instead of having to navigate over to CloudWatch.
Sometimes its difficult to determine the correct permissions needed for Lambda execution from other AWS services.
We do renew our use of Amazon Relational Database Service. We don't have any problems faced with RDS in place. RDS has taken away lot of overhead of hosting database, managing the database and keeping a team just to manage database. Even the backup, security and recovery another overhead that has been taken away by RDS. So, we will keep on using RDS.
I've been using AWS Relational Database Services in several projects in different environments and from the AWS products, maybe this one together to EC2 are my favourite. They deliver what they promise. Reliable, fast, easy and with a fair price (in comparison to commercial products which have obscure license agreements).
I give it a seven is usability because it's AWS. Their UI's are always clunkier than the competition and their documentation is rather cumbersome. There's SO MUCH to dig through and it's a gamble if you actually end up finding the corresponding info if it will actually help. Like I said before, going to google with a specific problem is likely a better route because AWS is quite ubiquitous and chances are you're not the first to encounter the problem. That being said, using SAM (Serverless application model) and it's SAM Local environment makes running local instances of your Lambdas in dev environments painless and quite fun. Using Nodejs + Lambda + SAM Local + VS Code debugger = AWESOME.
I have only had good experiences in working with AWS support. I will admit that my experience comes from the benefit of having a premium tier of support but even working with free-tier accounts I have not had problems getting help with AWS products when needed. And most often, the docs do a pretty good job of explaining how to operate a service so a quick spin through the docs has been useful in solving problems.
Amazon consistently provides comprehensive and easy-to-parse documentation of all AWS features and services. Most development team members find what they need with a quick internet search of the AWS documentation available online. If you need advanced support, though, you might need to engage an AWS engineer, and that could be an unexpected (or unwelcome) expense.
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.
AWS Lambda is good for short running functions, and ideally in response to events within AWS. Google App Engine is a more robust environment which can have complex code running for long periods of time, and across more than one instance of hardware. Google App Engine allows for both front-end and back-end infrastructure, while AWS Lambda is only for small back-end functions
Positive - Only paying for when code is run, unlike virtual machines where you pay always regardless of processing power usage.
Positive - Scalability and accommodating larger amounts of demand is much cheaper. Instead of scaling up virtual machines and increasing the prices you pay for that, you are just increasing the number of times your lambda function is run.
Negative - Debugging/troubleshooting, and developing for lambda functions take a bit more time to get used to, and migrating code from virtual machines and normal processes to Lambda functions can take a bit of time.