Amazon RDS Reviews

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.

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.

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.

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. 

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.

The primary use cases include storing transactional data for e-commerce, payments, and fintech transactions. It is used to manage and store various types of critical data in these domains.

The implementation of Amazon RDS significantly reduced our database management bandwidth by approximately 70-80%. 

The most valuable features of Amazon RDS include its managed service aspect, which simplifies the management tasks. The flexibility to choose between different underlying databases, such as MySQL and PostgreSQL, adds to its value.

The response time and the number of iterations required for the product's technical support could be improved. It could benefit from features that provide easier visibility into stale data and better recommendations for database optimization. Additionally, more seamless scalability, similar to what Google BigQuery offers, would be a valuable addition.

I have been working with Amazon RDS for about five to six years.

The product is highly stable. 

The solution is highly scalable.

The customer service and support are satisfactory, in line with other major cloud providers like Microsoft Azure. However, response time and the quality of initial support could be improved.

The initial setup was straightforward, primarily involving data migration and ensuring data integrity. The process took about two to three weeks.

Our in-house team implemented the product with guidance from AWS team. 

The platform pricing is on the higher side, but given its capabilities and ease of use, it remains competitive.

Amazon RDS is a reliable and scalable solution. It significantly reduces database management overhead. It is particularly beneficial for organizations that require high availability and scalability.

I rate it an eight. 

I use mostly the Postgres incarnation of Amazon RDS. Basically, Amazon RDS is a cheap database that is totally self-contained and self-managed, and that is its good part. There is also the downfall associated with the tool since you don't have you don't have root privileges or super-user privileges on Amazon RDS, so there are certain things you cannot do. Sometimes, when I really needed a database that I could have absolute control over, I used to spin AWS VMs and EC2 machines and load Postgres on that machine so that I could become a super-user. Amazon RDS is very useful for quick and dirty or for very established solutions where you don't have to develop or change a lot. Basically, you can you can load your data into Amazon RDS. In my data analytics space, I see Amazon RDS as an ancillary product to Redshift, which is the real workhorse in terms of big data, data warehousing, and analytics.

I don't manage my database with Amazon RDS. AWS manages Amazon RDS. Sometimes, it is enough, and I don't need to do low-level stuff, and I can use Amazon RDS. Suppose I really need to tweak and do low-level stuff, low-level in the sense of being very close to the system, and I need super-user privileges. In that case, Amazon RDS is out of the picture because AWS doesn't allow you to have super-user privileges in Amazon RDS. The use case for me with Amazon RDS is a cheap and dirty database that I can use when I don't need to do a lot of tweaking. When I need tweaking, I create my own instance of the Postgres, and I can become a super-user and do whatever I like.

As a customer of Amazon RDS, you don't have super-user privileges, and that is the only drawback where improvements are required.

I never tested the scalability of the product. I was scaling it up to two, three, and four gigabytes, and it was fine. I don't know how it fares when we are loading hundreds of gigabytes of terabytes of data. Redshift can manage huge amounts of data, but I don't know about Amazon RDS. I suspect Amazon RDS can handle huge amounts of data because Postgres is very capable of doing so. Amazon RDS in AWS is simply an umbrella. Underneath Amazon RDS, you can choose to implement MySQL or other databases. The implementation I always chose was Postgres.

I have been using Amazon RDS since 2017. My company has a partnership with Amazon.

AWS is a stable environment. Postgres is a very stable database. AWS implementation of Postgres, as far as I know, is very reliable. I never had any issues.

I never tested the scalability of Amazon RDS since it was, for me, a stepping stone toward having real analytics in Redshift. Basically, Amazon RDS was just a collector. I was collecting structured data into Amazon RDS, or if the data was unstructured, like in emails, I was using software to make sense of the email and then store the content of the email relationally in Amazon RDS. Amazon RDS was just a stepping stone, a part of the pipeline, just in order to collect the data momentarily so that the data could eventually be transferred across to Redshift.

The tool's technical support depends on your service level agreements with Amazon. If you are on the cheap side, obviously, they tend not to attend to your issues immediately, and I can understand that. If you pay a premium support fee, I don't know how Amazon treats you since I was never in a position to pay a premium support fee. Overall, I was never disappointed with the tool's support. I didn't face a lot of issues, so I never tested how good the support was because I have 35 years of experience in managing data. I tend to solve my own issues by myself.

The product's initial setup phase is totally easy. You go to a web page, configure your instance with checkboxes and drop-down list boxes, see what you want, see what your needs are, and what you are prepared to pay, compile a form with ten or fifteen fields, click on submit, and Amazon RDS is created for you.

Going from on-premise and hybrid into a complete Amazon RDS solution obviously frees up the need for DBAs. The fact that AWS manages everything for you means you don't need a lot of time and resources to manage the database. So you can cut your yearly salary for the DBAs in your company. You need to consider all the cloud costs as well. I believe it is cheaper to go with Amazon RDS rather than hosting Postgres instances in-house or on-premise. I know that AWS is becoming expensive. I really don't know where the breakeven point is between having your own Postgres instance that you manage yourself outside the cloud. Basically, there are three options. You manage your Postgres on-premise. You use an EC2 VM in AWS, and you install Postgres on it. You have the benefits of AWS scalability and security, but you still have your control, and you become a super-user on the database. The third option is to go with Amazon RDS, after which you lose control of your database, but you don't worry about managing redundancy and creating high-availability solutions because everything is done for you. I believe it is the best feature of RDS, which is total uptime guaranteed by AWS. You don't need to think about how to implement, test, and manage a high availability redundancy kind of solution, as everything is included in the package.

I don't know if the solution is cheap or expensive in comparison with competitors since AWS is the only cloud provider I tried so far. I connected some Azure Blob Storage to the instance running the Redshift instance. AWS is becoming pretty expensive because cheap or absolutely free services have become paid services. Amazon RDS is not an expensive product, but Amazon's ecosystem is becoming increasingly expensive.

In my experience, there is no need to maintain the product. I didn't try the tool's scalability. I was using the TRUNCATE TABLE command in every other ETL. TRUNCATE TABLE means I empty the data every time I load it. It was just a relational storage mechanism, basically, for a few gigabytes of data daily. Each ETL on a daily basis in the pipeline is used to erase what was there for the previous jobs and reload Amazon RDS, and when the loading in Amazon RDS was complete, there was another process in the pipeline that we used to bring the data across to Redshift. I never used it in a very sophisticated manner.

I have not tested the AI capabilities with the product. I know that a lot of the competition, whether inter or intra-cloud, is fierce nowadays, and AI solutions are popping up everywhere. I simply haven't had the chance yet to test the AI capabilities in AWS. It will be my next project.

The trade-off is between control and peace of mind. If you want control, and obviously, you cannot choose RDS. If you want peace of mind and you don't want to think about backing up the database or creating a high availability policy around it, then definitely go for Amazon RDS. If you have some, if you are a startup, for instance, testing new things, I wouldn't go for Amazon RDS simply because you don't have control over the database. If you are an established company and want to move from on-premise to the cloud, you have the once-off migration task from your on-premise into the cloud, and everything has already been concretized. The database that supports the application is already well-established. If you are not introducing new features or experimenting with the product to introduce new features, then Amazon RDS is a good choice.

I rate the tool a seven to eight out of ten.