Amazon Relational Database Service (RDS) vs. Google Compute Engine

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.

Incentivized

You can use Google Cloud Compute Engine as an option to configure your Gitlab, GitHub, and Azure DevOps self-hosted runners. This allows full control and management of your runners rather than using the default runners, which you cannot manage. Additionally, they can be used as a workspace, which you can provide to the employees, where they can test their workloads or use them as a local host and then deploy to the actual production-grade instance.

Incentivized

• 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

Incentivized

• Scaling - whether it's traffic spikes or just steady growth, Google Compute Engine's auto-scaling makes sure we've got the compute power we need without any manual juggling acts
• Load balancing - Keeping things smooth with that load balancing across multiple VMs, so our users don't have to deal with slow load times or downtime even when things get crazy busy
• Customizability - Mix and match configs for CPU, RAM, storage and whatnot to suit our specific app needs

Incentivized

• 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.

Incentivized

• Built-in monitoring via Stackdriver is quite expensive for what it provides.
• Initially provided quotas (ie. max compute units one can use) are very low and it took several requests to get an appropriate amount.
• Support on GCE is limited to their knowledge base and forums. For more hands-on support provided by Google, you must pay for their Premium services.

Incentivized

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.

Incentivized

Its pretty good, easy and good performance. Also, interface is very good for starters compared to competitors. Infra as Code (IaC) using Terraform even added easiness for creation, management and deletion of compute Virtual Machines (VM). Overall, very good and very easy cloud based compute platform which simplified infrastructure, very much recommend.

Incentivized

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).

Incentivized

Having interacted with several cloud services, GCE stands out to me as more usable than most. The naming and locating of features is a little more intuitive than most I've interacted with, and hinting is also quite helpful. Getting staff up to speed has proven to be overall less painful than others.

Incentivized

Google Compute Engine works well for cloud project with lesser geographical audience. It sometimes gives error while everything is set up perfectly. We also keep on check any updates available because that's one reason of site getting down. Google Compute Engine is ultimately a top solution to build an app and publish it online within a few minutes

Incentivized

It works great all the time except for occasional issues, but overall, I am very happy with the performance. It delivers on the promise it makes and as per the SLAs provided. Networking is great with a premium network, and AZs are also widespread across geographies. Overall, it is a great infra item to have, which you can scale as you want.

Incentivized

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.

Incentivized

• The documentation needs to be better for intermediate users - There are first steps that one can easily follow, but after that, the documentation is often spotty or not in a form where one can follow the steps and accomplish the task. Also, the documentation and the product often go out of sync, where the commands from the documentation do not work with the current version of the product.
• Google support was great and their presence on site was very helpful in dealing with various issues.

Incentivized

the online training & digital content available on the web from AWS was having sufficient information to deploy and run the service

Incentivized

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.

Google Compute Engine provides a one stop solution for all the complex features and the UI is better than Amazon's EC2 and Azure Machine Learning for ease of usability. It's always good to have an eco-system of products from Google as it's one of the most used search engine and IoT services provider, which helps with ease of integration and updates in the future.

Incentivized

It works really well with other Google Cloud services, making it easy to build scalable solutions across different teams and locations.

Incentivized

• The overall cost increases, but we spect this and we can mitigate other risks.
• Is easy to work from the cloud. Is reliable, but we keep our local solution as well where RDS works quite good.
• RDS allow us to focurs on owr objetives instead of the other matters regarding databases.

Incentivized

• With Google Compute we don't have the overhead of managing our own data centers reducing costs and reducing the staff needed to manage systems.
• As I said earlier, Google's costs are ~1/2 of AWS, so we are able to see a ROI much faster.

Incentivized