Amazon RDS Reviews

Amazon RDS is typically used for AI applications. I am developing it for an AI recruitment agent and for collecting data for HRIS, Software as a Service for a workforce as a service, and storing data.

The features of Amazon RDS that I have found most valuable and useful so far are its fully managed service, point-in-time restore, and other serverless features such as snapshots and backups, which have eased my job to manage databases.

The automated backups of Amazon RDS help in data recovery by mitigating disaster recovery. I can revert to the nearest time if there is any data corruption or other issues, and this helps tremendously.

I assess Amazon RDS's read replica feature for improving application performance as good. For standby nodes in Amazon RDS, I am using them for high failover, and so far it has been performing well.

I have used Amazon RDS's Multi-AZ deployments, and it helps enhance data availability by providing high failover. It enhances high availability for my application as well.

I think Amazon RDS can be improved or enhanced if it can be implemented with other monitoring tools such as Percona. Currently, I am trying to add Percona monitoring for monitoring in addition to its own built-in CloudWatch. Amazon RDS should allow third-party software like Percona for monitoring.

I have been working since 2022 with Amazon EKS, and I am using it for Kubernetes service on AWS.

I evaluate the stability and reliability of Amazon RDS as quite good. So far it has been performing well.

So far, I have not had any outages, crashes, or downtime.

For performance metrics, I have observed log queries, queries, and query analytics.

I do not often communicate with the technical support of Amazon RDS, not really recently, but for other cases such as billing, I think it is quite good.

I would rate the technical support of Amazon RDS as seven out of ten.

Before Amazon RDS, I used different solutions for the same use cases, such as self-managed databases. I have been using CNPG, which is a CNPG cluster for Kubernetes.

I participated in the initial setup of Amazon RDS, and from my perspective, it is quite detailed, but there are no problems at all for configuring, and there were no challenges.

I decided to switch from the previous solution to something else because there is manual configuration that mostly makes my databases unreliable. I think a self-managed database is the best choice.

I leverage Amazon RDS for web applications.

I think the pricing of Amazon RDS is a little bit more expensive, but in return, it has good performance, so I have nothing to say.

I would rate this product an overall eight out of ten.

I am a Solutions Architect, so I design solutions for our clients. Prior to this role, I was an implementation engineer, so I also implement solutions for our customers.

Amazon RDS's main strength is that it is a managed service. Aurora, the RDS product, is excellent. It provides multi-AZ and multi-region support for read replicas.

For a global scale company, I believe this is a very critical and good feature.

Amazon RDS also has PITR, which is Point-In-Time Restoration. I can select any timestamp that I want to restore to.

High availability is a basic fundamental architecture requirement. Multi-AZ automatically complies to that requirement, so that is a very helpful and useful feature.

IAM has multiple authentication mechanisms. Based on whatever is needed by the customers, it can be easily integrated. It supports Kerberos for Microsoft SQL, easy integration with local password, or IAM secret manager. Many integrations are available, so it is very helpful.

Currently, I cannot think of any major improvements. Perhaps more platforms in terms of database engine versions would be beneficial. Right now, Amazon RDS supports MySQL and PostgreSQL, but there are certain other RDS engines that it cannot support yet. If Amazon RDS could support more engine versions, it would be better.

I am from an AWS Premier Tier Partner organization. Amazon RDS is acceptable for our needs. All of our customers use Amazon RDS because that is what my company does. I believe the review rating for this product is 9 out of 10.

I am working on DevOps, tools, Kubernetes, and Docker. I work with Docker on CentOS. I have been working with Docker on CentOS.

We are using AWS tools almost exclusively. Currently, we are not using Amazon RDS, but in the past two to three months ago, I have built it during university projects, helped final year students, and taught some students to solve their problems and parts of problems that encourage and help in their projects.

I have been working with Amazon RDS for 6 months. We are using MySQL, PostgreSQL, MariaDB, Oracle, and SQL server for Amazon RDS. Customers usually use Amazon RDS for database authentication and production accounts, secrets manager parameters, stores, and making RDP passwords.

The features of Amazon RDS that I have found most valuable include web and mobile applications, enterprise applications, data warehousing and analytics, and software as a service platforms, along with dev testing environments, disaster recoveries, and backups.

The mobile app backend and development environment is also the best feature for database management for my customers.

Database management is effective in Amazon RDS because it offers automated backups, high availability, read replicas, and support from multiple database engineers, while also providing security, monitoring and metrics, scalability. We are using snapshots and database migrations as well as performance optimization.

The impact of Amazon RDS scalability and backup has been positive, with good vertical scaling, scale up and down, horizontal scaling, and storage scaling. The performance was good and availability helped with reducing downtime.

User interface needs improvement for using IPS and cloud watch to scale and utilize read replicas, enabling performance insights to view query formats where the bottlenecks occur, identifying the fixes, slow queries, and missing indexes, improving the security and monitoring with alerts.

Stability could be improved with pre-built infrastructure automation tools such as Ansible, which can reduce setup times significantly.

I have been working with Amazon RDS for 6 months.

Deploying Amazon RDS does not take much time; daily automated backups and snapshots can be done in 5 to 10 minutes to provision a DB instance, with 1 to 3 hours for installation and configuration.

On-premises setups take much longer; it can take 12 to 13 hours to install, as opposed to the efficiency of Amazon RDS.

I would rate how stable Amazon RDS is as seven. When discussing a rating of seven for stability, I am referring to on-premises setups.

I would rate the scalability of Amazon RDS as nine.

The official AWS technical support for Amazon RDS is helpful, providing 24/7 assistance for all business support cases with tools such as the health dashboard and AWS trusted advisor.

I would rate the technical support from AWS for Amazon RDS as nine.

Positive

I would rate the initial setup of Amazon RDS as eight.

I have a services agency and we provide solutions and support for university projects and also solve their problems. Stability could be improved with pre-built infrastructure automation tools such as Ansible, which can reduce setup times significantly. My official email address is bc170202097@vu.edu.com. The link can be sent to my private email address bakir75@gmail.com. Overall, I rate Amazon RDS an eight out of ten.

We are working mostly with the infrastructure being totally on AWS, so we are using AWS services, RDS, MySQL, Postgres, all the databases, mostly Oracle, and then Databricks and Snowflake. We are into using only cloud-native services, not any other software.

In terms of the main use cases, we are working in a product company that is heavily into the intellectual property domain data. We basically acquire data from various patent offices and provide the data as a service on top of that to various clients. We are using AWS and RDS for storage of all this metadata and churning out some important information out of that by applying certain transformations on top of this data.

The biggest advantage of Amazon RDS, which is basically an AWS service, is that you can customize it. Amazon RDS is your RDBMS on AWS. For example, if you want to have MySQL or if you want to have Postgres, those RDBMS on AWS, then you need to go with Amazon RDS. When you configure Amazon RDS, you choose which RDBMS software you want to install on that, be it Oracle, MySQL, Postgres, etc.

We are using automated data backup in Amazon RDS.

In some cases, we are using the read replica feature, and it does improve our application performance because we do not allow any downstream system to come to the main storage or main databases and perform a query. Rather, we create the replica, which is a downstream system that keeps updating from the main database. We open the replica for the downstream systems to perform any heavy queries on the data rather than giving direct access to the database.

I don't really see any disadvantages of Amazon RDS. With Oracle, I think AWS doesn't provide the RAC stability. If you have Oracle installed in your own data centers, you can set up various clusters and we can set up the RACs, but in Amazon RDS, we cannot have the RAC feature of Oracle. They could add that feature.

Amazon RDS has limitations regarding RAC. If we talk about installing Oracle in RDS, we cannot have the RAC, but if you deploy Oracle on GCP, then there is probably the RAC feature available. I observed that around two or three years back, but I'm not sure whether they have added the RAC feature in AWS.

Amazon RDS is expensive compared to GCP. GCP also has the same features, and although it is quite extensive and feature-rich, I see Amazon RDS as slightly expensive compared to other clouds.

Amazon RDS is quite stable, and the SLAs are sort of 99.98%.

The installation of Amazon RDS is quite easy and quite scalable. We are using Terraform for all infrastructure deployments, so we build the Terraform, deploy it, and it spins up the RDS with the provided features and securities in templates.

The support from AWS is excellent and very good.

I would rate the support from AWS very high, maybe nine, but it also depends on what kind of support you have signed in your contract, whether the premium support or the standard support.

Positive

The integration of Amazon RDS with AWS IAM is pretty simple and does positively affect our data security.

I am not heavy into AWS because we have a separate team for that, which is the cloud engineering and cloud architects, so they take care of all that stuff. We have the Multi-AZ availability zones and we also have the DR sites.

I do not really work with Microsoft products overall, but I have worked on the Power BI in terms of the BI products, but not on other Microsoft products.

I won't rate myself an expert on AWS. Although I have worked on AWS, there are different teams, the architects team and engineering teams in AWS, whereas I'm from the application side.

My email is Vishal.Goyal@Clarivate.com, and my job title is Director of Software Engineering.

On a scale of one to ten, I rate Amazon RDS a nine.

The primary use case for Amazon RDS is to optimize database management. The technology is utilized to ensure high availability, deploying the RDS technology across multiple availability zones for better fault tolerance and minimized downtime. 

Its use case is critical for applications that require high availability. Additionally, it is valuable for scalability with features like read replicas and storage auto-scaling, allowing easy scaling with increased users.

Amazon RDS provides data encryption using services like KMS, crucial for securing high-sensitive data and meeting compliance requirements such as HIPAA or PCI DSS. 

The best practices we've employed with RDS help design a well-architected framework, encompassing security, encryption, scalability with multi-availability zone deployment, and operational excellence with automated backups. RDS features, such as reserved instances, storage auto-scaling, monitoring with technologies like CloudWatch, and proxies, contribute to cost optimization. 

The solution enhances security with IAM authentication and offers high availability to end users.

For improvements, Amazon RDS could work on more features for multi-availability zone deployment to enhance higher availability, and on simplifying migration for those transitioning from on-premises to cloud environments. Improved data migration services would enable easier transitions to the cloud.

I have been using Amazon RDS for close to a year.

Amazon RDS is very stable when deployed correctly across different zones with the right configurations. This setup ensures the database continues to operate even if one zone faces issues, maintaining business continuity and user access.

Amazon RDS excels in scalability, and I would give it a ten out of ten. Its automated scaling, both in storage and instances, is vital as it eliminates manual interventions. The system is reliable in handling fluctuations in user demand.

The initial setup process of Amazon RDS is straightforward if you follow the deployment steps carefully, which includes selecting the database engine, configuring storage, and setting up networking. I would rate the ease of setup as eight out of ten due to the need for customization.

I find the pricing of Amazon RDS fair, as AWS operates on a pay-for-what-you-use model. Auto scalability helps handle varying demand, making it cost-efficient without overprovisioning resources.

For anyone considering Amazon RDS, it's critical to learn about the technology and understand why you want to use it for solving particular problems. RDS is a go-to solution for database management due to its automation, scalability, and security. 

On a scale from one to ten, I would rate Amazon RDS overall as nine. It is an excellent choice for managing relational databases with its comprehensive support for automation, scalability, and security.

I used S3 bucket to save files. Additionally, I used the SQL database.

S3 is Simple Storage Service, which we usually utilize for specific purposes. For example, we created a system where we share videos and photos where we comment and produce work. In the backend, we save the files that are loading in the S3 bucket, and that link is provided to the front end for displaying the image. That is why we use S3 bucket for storage purposes. It serves as a simple storage solution.

Regarding Amazon RDS in AWS, it is easy to use. It is somewhat pricey, but manageable. It has easy tasks, and we can easily integrate it with frontend components. For example, with IDE services, you can use tools such as pgAdmin. The installation steps are straightforward, and availability is high for these reasons.

Amazon RDS is the database service we have been using for approximately four to five years. It is a standard Postgres relational database that we use for storage purposes.

Amazon RDS is good to use, with pricing being the main challenge. Compared to other services such as DigitalOcean, it has minimum pricing but costs slightly more.

The backup and restore processes take more time compared to other providers. For instance, if DigitalOcean takes two minutes to restore or create a backup, AWS will take 2 to 3 minutes. There are also more steps to follow compared to other service providers.

We have been using Amazon RDS as our database service for approximately four to five years.

The service is stable without any significant issues.

It is easy to scale, and we can migrate from one system to another with ease.

We receive adequate support for our needs.

Positive

The installation process is straightforward without complex requirements. We can directly select the desired database, specify the required memory, and set the port number for connection. Everything is easily configurable.

Returns on investment depend on client requirements. They charge based on the services we use, and billing is determined by our usage.

I have used S3 bucket and Backup services.

I have utilized Amazon RDS, Relational Database Services, and EC2 (Elastic Cloud Compute) from Amazon. These are the three main services I have experience with.

Amazon RDS is a product that offers various relational database services. It includes DynamoDB for NoSQL databases, as well as MySQL and Postgres for relational databases. We use it primarily for its backup capabilities, allowing us to recover data immediately if needed.

While we haven't used AI for Amazon RDS, we implement AI services for Git-related tasks, particularly during PR (Pull Request) reviews to check if coding standards are maintained.

Based on my experience, I would rate this solution a nine out of ten.

I use Amazon RDS to support scalability, with multi-AZ support being an essential aspect. It offers a managed service that simplifies my work significantly. I use it across multiple companies, supporting all scalability and availability needs.

The most valuable features of Amazon RDS are its availability and security support, which are crucial for managing the system effectively. Additionally, the scalability is impressive as it allows configuration and expansion quickly. It simplifies the process of scaling, especially when transitioning from MySQL to Amazon RDS. Before, I maintained scaling myself, but with Amazon RDS, tasks like in-place scaling of CPUs and memory are efficiently handled.

One key improvement would be adding support for multi-storage paradigms, including columnar support, as seen in TiDB. The serverless support with Aurora could also be enhanced. Additionally, having native Change Data Capture (CDC) support would be beneficial, allowing for seamless integration with Kafka without relying on external technologies like Debezium.

I have been working with Amazon RDS for more than ten years, having used it since its inception across multiple companies.

I would rate the stability of Amazon RDS a nine out of ten. It is a stable product overall, with very few issues.

Despite being a strong feature, scalability could be improved due to the lack of full functionality in autoscaling. I rate it seven out of ten.

The technical support from Amazon could improve. I would rate them a six out of ten as they do not fully meet my expectations.

Neutral

I previously used MySQL, and transitioning to Amazon RDS improved my scaling operations significantly.

The initial setup of Amazon RDS is straightforward and fully cloud-based.

The pricing for Amazon RDS is reasonable.

I moved one of my use cases from Amazon RDS to TiDB due to its multi-storage paradigm and better serverless support.

I rate Amazon RDS an eight out of ten overall. Although both AWS and Google have similar offerings, if given a choice, I prefer AWS. The integration with AI technology could be improved as well, and I recommend exploring TiDB's approach of allowing natural language queries for SQL, which Amazon RDS currently lacks.

I am using Amazon RDS and CDMS clients for monitoring databases. I have set up multi-level servers for data collection and application development.

Amazon RDS makes it easier for me to manage databases compared to traditional databases like MongoDB or local host servers. It offers an easy-to-use interface that allows me to monitor instances and update necessary features conveniently. This convenience is significant for both local and remote data management.

I do not have any specific areas for improvement as I am still in the initial stages of using Amazon RDS.

I have been using RDS for the past two years on a personal level and for the last three months at a company as an intern.

I only encountered stability issues twice when setting up the multi-layer RDS servers, which were resolved through AWS resources.

I have not experienced any scalability issues while using Amazon RDS, and the solution meets my needs for both local and remote data management.

I previously used Microsoft Azure for application development. I switched to AWS due to more affordable pricing over long-term plans.

The initial setup depends on the complexity of the applications. While it might be a bit challenging for multi-level applications, single or double-step setups are straightforward.

AWS is affordable compared to Microsoft Azure. While Azure provides great services, long-term plans on AWS are 20% to 30% cheaper.

I evaluated Microsoft Azure and currently explore IBM Cloud Services.

I recommend RDS to anyone who asks me about it. 

On a scale of one to ten, I would rate Amazon RDS as eight.

We are more on the development side of it. We develop software using RDS.

So, use cases are specific to our clients. We work for our clients, so whatever use cases they have, we generally support them on the cloud. Mostly for transaction processing of the application software that we develop for our clients. It could be in the health care domain, transport domain, or anything like that.

It's a fully managed database, so that makes our life easier from the operational standpoint. That is the key, basically.

Mostly from the operational standpoint, it is fairly easy to scale disaster recovery and all that. It becomes easier while we use Postgres and MySQL flavors of it. So whatever benefits we get from those databases are in addition to what AWS provides as a PaaS solution.

There are some use cases that might come up where we would want to understand the performance aspects better, especially in the order of Lambda for a multitenant kind of database or structure, where you have several tenants with isolation in place. That's one thing we look forward to better understanding and providing as a service to our clients.

I (my company) has been using it for four to five years. We use a complete list of AWS products, including S3, RDS, Kafka, MSK, and all that.

I didn't come across any glitches or latency. It has been stable for my use cases.

It is a scalable product. 

We get all the technical support needed from AWS. It's very good. 

I have seen mostly pros with RDS compared with some other databases like Postgres. 

So, the pros in terms that it is fully manageable and scalable.

The limitations are given and stated already, so we have to take them into consideration while designing our solutions.

Some of the services are pricey, but, in general, this product is affordable.

Overall, I would rate it an eight out of ten. 

Amazon RDS is my primary database. I store and perform CRUD operations in it.

We used to have a separate database. We managed everything, including scaling. We faced memory issues when there were too many hits, so we manually increased or cleaned the memory. Amazon RDS is automatically scalable. No intervention is needed. Upscaling and downscaling happen automatically.

Now, we have tighter controls. Earlier, we had roles mapped with AD integrations to the server where the database is. We used to do a lot of work. Now, we have IAM integration. If a person has a particular IAM role, they can access it. Amazon RDS has good authentication, operation, and autoscaling. It has features similar to an ordinary database. We get to do the same job without worrying about the infrastructure.

Authentication, authorization, and autoscaling features solve half our problems. The integrations are good. When a record comes, I can create a DB trigger. I can store it in S3 buckets. We cannot do it in a traditional database. We will have to run a separate script for it.

We can connect the solution with multiple databases. The vendor is adding all kinds of databases to it. The data protection is good enough. The product solved our DevOps and admin problems. We can add RDS integration with CloudWatch to provide metrics on the database instances. We can do some customizable metric evaluations. We can fire requests with EventBridge depending on events.

The product should support new databases. RocketDB is written in C++. It is useful when we work with Kafka. The product should support more databases and not just the standard four to five databases. It will help the users to explore new avenues and not be confined to the standard ones.

The tool provides automatic backup, but the recovery is slow if something goes wrong. We need to wait for some time. If a failure happens, recovery takes some time. Meanwhile, we lose business. It would be great if it happens much faster. The cross-region replication settings are very complex. We need to do careful planning.

I have been using the solution for more than five years.

I have seldom faced crashes in AWS. I didn't face any issues with stability. I used to face stability issues four years back. Occasionally, crashes happened, but we had an automated snapshot feature. We could get back up from there. Occasionally, the vendor has a maintenance window during which they change the underlying infrastructure. Sometimes, due to some incompatibility, we face crashes. Otherwise, it is good 90 to 95% of the time.

The scalability is very good. The tool automatically scales up. It’s a relatively simple setup.

The initial setup is easy.

The licensing model changes often. The prices for different regions are different.

We are customers and partners. I recommend the product to others. It is a great tool. Overall, I rate the product an eight out of ten.