Amazon Aurora Reviews

Amazon Aurora is a service provided by AWS, and we received support from AWS for our implementation. The direction we are moving toward is specifically Amazon Aurora PostgreSQL.

The functions I have found most valuable in Amazon Aurora PostgreSQL are features that are not available in normal RDS PostgreSQL, particularly for scaling and restoration purposes in the event of failure. Amazon Aurora PostgreSQL has implemented these features with more processes, speed, and performance improvements. This is the key reason we stick with this flavor.

The main benefits my company receives from Amazon Aurora are performance and cost.

The automated backup feature has helped me with the data recovery process. Initially we faced challenges, but now it is very stable. We continue to rely on this feature.

Amazon can make better access levels and reduce costs for Amazon Aurora. A cost reduction would support multiple teams to adopt this solution since the cost is currently higher. Comparatively, we have the feature of scaling and everything we need. If you launch PostgreSQL on-premises, you need to have a separate DBA for maintenance and everything. If Amazon reduces the cost of Amazon Aurora, it would support large team adoption.

A great feature to see in the next version of Amazon Aurora would be improvements in vectorization. In our PostgreSQL, we have pg_vector that helps with vectorizing many of the tables and that is used for data science projects. If Amazon improves this vectorization, it would be much more useful for data science and AI projects.

I have been using Amazon Aurora for three years.

I would rate the stability of Amazon Aurora as a nine out of ten.

Regarding scalability and the ability to scale, I would give it a 9.5 out of ten.

I would rate Amazon's technical support as a nine out of ten.

My feedback about the migration capabilities of Amazon Aurora is that initially we did a migration from on-premises to RDS directly. Later on, we moved from RDS to Amazon Aurora. I have not done a direct migration to Amazon Aurora in my project.

I would say the initial setup for Amazon Aurora is medium. We still have scope for improvement to simplify the process.

I have compared Amazon Aurora with other products. Amazon has its own flavor of PostgreSQL, which is Amazon Aurora. We also have RDS itself and RDS PostgreSQL, which is the initial flavor and also a competitor product, as well as MySQL. These two are the flavors and direct competitor features available within AWS itself.

I am still using data migration services and database migration services, and so far, the migration is completed and we are stable now. The migration task was done and we are working with AWS products and everything is working well for me.

Nowadays, I am mainly working with Amazon Aurora, specifically RDS Aurora and S3.

In the cloud, we mostly adopted the serverless feature as well. Other teams have implemented serverless, but in my team, we have not implemented this serverless feature.

I purchased Amazon Aurora through the AWS portal.

I would rate this review overall as 9.5 out of ten.

Today, some customers need to migrate and convert Oracle databases to Amazon Aurora. Amazon Aurora for PostgreSQL or MySQL Aurora is very common. I have two customers who made a study about this conversion.

The industries of my customers using Amazon Aurora include finance and services, particularly related to payments.

The deployments for Amazon Aurora are for enterprise and middle companies.

I have two customers who are studying to convert their database for a newer, modernized application. For example, I have a batch process, and these customers can change the API process. They need to create a new process to change from batch to API or microservices.

I use the AWS Schema Conversion Tool for changing the schemas with Amazon Aurora. In most cases where the customer doesn't have a maintenance window, I use the AWS Database Migration Service for changing all the data and transitioning to the new environment with Amazon Aurora.

Amazon Aurora's best features are about scaling up and scaling down, which is perfect. This database has many options for tuning, and it's possible to adjust according to the needs of the customers. It's a great database.

The automated backup feature is effective. A nice feature is that last week, I made a snapshot of my MySQL database, and I restored this snapshot and migrated it from MySQL to Amazon Aurora MySQL. It's perfect.

Amazon Aurora's scaling up and scaling down is helpful for cost efficiency because the cost is more controlled. For example, when I need one cluster for two nodes, if I have a special week, I can scale up. For one hour, I can create a scheduled automatic scale, and when this period finishes, all capacity goes down.

With Amazon Aurora, you can have more control over money regarding FinOps.

I don't use the automated backup features with Amazon Aurora currently, but when I made this project for migration or conversion, I used the backup options in Amazon Aurora for cloning databases. It's very common.

I don't use Amazon Aurora's global database feature; I just use the local feature.

I am not directly familiar with Amazon Aurora as I have other coworkers who use it with other clients, and they can speak about this product.

I have dealt with the support for Amazon Aurora.

I rate the support for Amazon Aurora as an eight out of ten.

Positive

The return on investment with Amazon Aurora depends on the customer. In many cases, the customer has a reserved instance for saving their investment, which depends on the project.

The pricing for Amazon Aurora is different from DocumentDB because DocumentDB is cheaper. However, when you manage the administration more closely, you can control costs better with Amazon Aurora. With DocumentDB, you don't have many controls as the process is automatic. But with Amazon Aurora, you can adjust memory, queries, and other variables for more control.

I use Amazon Aurora, and my customers use it as well.

Licensing applies to this solution.

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

Neutral

The migration process to Amazon Aurora is the best part; it's one of its key strengths, as we hardly had any hiccups during migration, which was very smooth and pretty straightforward given our data was mostly in English.

The functions I've found most valuable in Amazon Aurora include not needing to take care of partitioning or managing the size of the database, as we just migrated from MySQL to Aurora, and all that is managed internally, which was one of the main use cases for us.

The automation backup feature is not useful for me right now because we are using Amazon Aurora only for the lookup database, which will not grow too large, it would be only a few thousand rows, so we're not considering automation of any backups at this point.

The auto-scaling capabilities in Amazon Aurora are enabled, and since the database is not going to exceed 2 GB in size, maintaining a diverse set of databases for integration with third-party vendors is the reason we wanted to have one common lookup accessible to everyone via APIs or SOAP calls.

I would like to see some tutorials from Amazon for Aurora because I'm too new to it.

I believe Amazon can make more tutorials for the product since there's a lot of reading required, and a short tutorial of maybe two to three minutes would really help.

It's too early for me to say what Amazon could improve for Aurora because it's just been a couple of months.

I would rate the stability of Amazon Aurora a 9 or 10 because the main point is we are not using it extensively for high value or high throughput transactions, so the hit rate is pretty low.

I rate the scalability of Amazon Aurora a 9, since it is a managed service that performs well in that aspect.

The technical support from Amazon is kind of out of my scope since the infrastructure is handled by another person, so I don't perceive any issues in that area as they can directly contact the support team.

Positive

I have moved on from Kofax and am now a Solution Architect, technology agnostic now.

The initial setup process for Amazon Aurora was simple because we did not do much customization, and our in-house infrastructure guy set up the VPN, so we just had to stand up the Aurora instance.

I don't have exact comparisons with other vendors for Amazon Aurora, but in our migration, the cost was a major factor, as AWS is less expensive compared to Azure, despite Azure's beautiful services and interfaces.

On a scale of 1-10, I would rate Amazon Aurora a 9.

I have an application where I shifted from Oracle to Amazon Aurora. My primary use case involves moving my applications and services to Aurora.

The most valuable features of Amazon Aurora include the global instance with the global writer endpoint, which allows failovers and instance switches without requiring changes in my code, thanks to the default global Route 53 endpoint. 

In Oracle, I had to update the endpoint whenever I switched my database from one region to another. Scalability is excellent, as I used to face space issues with Oracle, whereas with Aurora, I haven't encountered such issues.

The main improvement needed is the lack of a comparison tool in Aurora. In Oracle, tools like Veridata allow for comparing databases and certifying data accuracy, even offering repair capabilities, which are missing in Aurora. There should be a similar comparison tool in Aurora.

I have used the solution for two years. From February 2021.

A challenge with stability is the lack of long-term log retention. They don't retain logs for more than three months by default, and if an older issue arises, troubleshooting is difficult due to a lack of logs.

Scalability is excellent. I don't face space issues that I encountered with Oracle. I rate it eight out of ten or nine out of ten.

Customer service is good. I have premium support from Amazon, and they assist me efficiently through chat and direct support.

Neutral

I used Oracle Database previously and switched to Amazon Aurora. The switch was primarily due to cost considerations, as moving to Aurora saved me approximately five thousand dollars per month. 

Another factor was that Aurora includes built-in replication capabilities without requiring separate services like GoldenGate in Oracle.

The initial setup was smooth, and I didn't encounter any challenges. I found it manageable and able to complete it successfully.

Cost-wise, switching to Amazon Aurora is beneficial, saving me around $60,000 per year.

There are no license costs associated with Amazon Aurora, only costs for memory, storage, and usage. I used to pay different rates for Oracle in different regions, which is not an issue with Aurora.

My advice is to spend time initially on migration, as services like database migration services are now available to ease the process. Aurora offers many nice features and good scalability, with improvements in migration processes. 

I rate the overall solution at eight out of ten.

I primarily use this service for general SQL and PostgreSQL databases. They now offer some really good scaling and limitless versions that are available to me, which I find very impressive.

I think it's a good service, and it has gotten better over time. I can see the improvements immediately and after some extended use.

I believe offering people the option to use Graviton processors or not is important, but they should just have people use the Graviton processors and the more advanced chips to save money. Sometimes mistakes can be easily made, and people can waste money by mistake if they do not know what they are doing.

I have been using this solution for probably about four years.

I find it very stable.

The scalability has gotten much better throughout the years. Now, if I have the ability to get the limitless Aurora, I would rate it ten out of ten.

Microsoft can get expensive. I have used MariaDBs for a lighter version or just MySQL light. It depends on what my application is.

The initial setup is pretty easy. It depends on how complex my database is, but it could take a day or two to set up, especially if I am migrating data. If I am using infrastructure as code to set up my database, it does not take too long to spin up a database.

Usually, the engineers handle the implementation. I am a solutions architect, so it is generally the data specialists, the engineers who end up doing it. It depends on who writes the infrastructure as code and who programs the database, handling the rows and tables and all of that.

I think the pricing is fair.

My advice would be to read the documentation and become familiar with how it works and how to set it up properly. I would probably rate it about an eight out of ten.

One of the use cases is as a data store for applications using the Oracle database engine. The customer used Oracle for years as a self-managed database, however, AWS manages installation, maintenance, and backup, reducing the workload for the customer. It is especially convenient for database administrator activities, patching, and hardware management.

One of the most valuable features is storage scaling. Depending on storage requirements, AWS enables auto-scaling of storage. In non-AWS environments, adding storage typically requires downtime. 

Furthermore, AWS provides out-of-the-box monitoring for performance to ensure there are no performance bottlenecks, and offers the option to switch to higher performance storage for improved performance. 

Another advantage is that with AWS handling administration, responsibilities like database provisioning and maintenance are significantly reduced. Customers can create services and start using them immediately without worrying about managing hardware or creating databases.

AWS RDS doesn't provide an option to apply one-off patches, which can be critical for business due to unexpected product bugs. While self-managed systems allow immediate patch application, RDS has limitations on patch application and scheduling, which doesn't guarantee inclusion of urgent patches.

I have been using it for more than five years.

Amazon's support is good. When issues arise, it's easy to reach someone, especially with an enterprise-level support model. However, for personal accounts, getting support is challenging.

Positive

Oracle was used previously as a self-managed database. AWS offers a managed solution, which is appealing due to AWS handling heavy lifting tasks, such as administration and maintenance.

The setup is fairly straightforward, especially when migrating from the same database engines, avoiding complex changes. AWS's Data Migration Services adds to the ease of initial setup.

AWS is costlier than self-managed solutions, but this includes the managed service experience. Their pricing is fair and reflects the managed service and additional features AWS offers.

Look at the limitations before you start with this product. Understanding AWS's documented limitations helps avoid surprises later. I would recommend Amazon Aurora to others.

I'd rate the solution eight out of ten.

We are using AWS mainly for EC2 virtual machines, Terraform for automation, and database services. We utilize AWS services for DevOps, creating CI/CD pipelines through Terraform. 

We connect virtual machines to databases. In terms of databases, we use RDS, primarily PostgreSQL, and sometimes use Aurora. We also engage in monitoring and optimizing database performance using AWS tools like CloudWatch.

Aurora is a key pillar for us, offering performance and availability. It is faster than RDS and supports multi-region clusters and scalability. 

One feature we value is Aurora's ability to provide a reader endpoint, allowing applications to connect without tracking replicas. It supports auto-scaling and offers several options for monitoring and optimizing database performance. 

Aurora's fault tolerance and ability to handle multiple replicas contribute to its reliability and high performance.

Currently, I am unsure what aspects of Aurora require improvement. The solution meets our needs in terms of high availability, durability, and backups. However, room for improvement might be in the UI, integrations, or data working capabilities for better user experience.

We have been working with Aurora for three to four years.

Aurora provides high stability and performance at a global scale. It offers high availability for Aurora MySQL and PostgreSQL engines and manages high-performance demands effectively.

Aurora is highly scalable, supporting both high-performance and high-throughput requirements. It easily adapts to increased usage and scales across multiple regions.

I rate AWS tech support highly, around an eight to eight and a half out of ten. They offer extensive support, which aids in managing Aurora effectively.

Positive

Currently, I am working on a Microsoft project and mainly use AWS Aurora. We also use Power BI and Kusto database services. Compared to these, AWS Aurora offers a more seamless experience.

The initial setup involves creating database services, usually handled by the admin team. If they are unavailable, our team manages it, though there are challenges, our team ensures smooth setups.

The implementation involves a team of five members, including myself, handling all database-related tasks.

The benefits of Aurora include better performance than traditional databases, supporting MySQL and PostgreSQL engines, providing managed backups, and offering high fault tolerance. Aurora ensures data reliability and high availability, crucial for operational efficiency.

The price of Aurora is generally reasonable. It fluctuates based on performance levels and usage, yet maintains a good balance with our operational demands.

We have compared Aurora with DynamoDB for scalability, performance, and availability. Aurora is the preferred choice for our requirements.

Aurora is the best service within AWS products for our needs. It offers great ease in creating snapshots, backups, and managing databases. I rate Aurora nine out of ten, acknowledging room for improvement, yet recognizing its extensive benefits.

We had a project in Germany where we needed to design a comprehensive AWS solution. We used Amazon Aurora because the existing database on-premises was set up in such a way that Aurora's functionality was more efficient.

Amazon Aurora has significantly improved our organization's database management due to its speed and efficiency. The use of Aurora has resulted in faster query execution times, enhancing our overall data processing capabilities.

What I like most about Amazon Aurora is its speed and efficiency. It is faster compared to RDS, and even compared to on-premises databases, making it better in terms of performance and cost-efficiency.

When using the serverless version of Amazon Aurora, I encountered issues such as the inbuilt query editor not being available. This was a challenge when I had to use alternative tools like PG Admin to manage queries.

I've been using Amazon Aurora for a couple of years now.

We faced a few bugs initially, but with the help of official documentation, Google, and ChatGPT, all issues were resolved. Overall, the system is stable.

Amazon Aurora is highly scalable. We manage large amounts of data effortlessly, and its scalability was crucial for our versatile ecommerce site. We implemented auto-scaling for our EC2 instances, which worked flawlessly.

Before Amazon Aurora, we used various databases, both SQL and PostgreSQL based. We switched due to Aurora's efficiency and better performance, particularly in handling complex queries.

The initial setup was slightly complex as I had to reference documentation to make choices, but it wasn't overly challenging compared to legacy systems.

Amazon Aurora is cost-efficient compared to previous on-prem databases, offering excellent speed and performance for the costs incurred.

We previously used on-prem databases, Redshift, and Snowflake for data warehousing before switching to Amazon Aurora.

I highly recommend Amazon Aurora to others, as it has proven effective for us in various projects, even those requiring significant architectural considerations.