Amazon Aurora

Amazon Aurora

Score 8.7 out of 10
Amazon Aurora


What is Amazon Aurora?

Amazon Aurora is a MySQL compatible relational database system from Amazon Web Services.
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What is Amazon Aurora?

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, built to combine the performance and availability of enterprise databases with the simplicity and cost-effectiveness of open source databases. The vendor states Amazon Aurora is up to 5X faster than MySQL databases and 3X faster than PostgreSQL databases, and that it provides the security, availability, and reliability of commercial databases at 1/10th the cost.

Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).

The vendor invites readers to learn more details on how they designed Amazon Aurora, from AWS CTO, Werner Vogels.

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Frequently Asked Questions

Amazon Aurora is a MySQL compatible relational database system from Amazon Web Services.

Microsoft SQL Server, Oracle Database, and PostgreSQL are common alternatives for Amazon Aurora.

Reviewers rate Support Rating highest, with a score of 9.8.

The most common users of Amazon Aurora are from Enterprises (1,001+ employees).
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(1-17 of 17)
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Score 9 out of 10
Vetted Review
Verified User
Amazon Aurora is a great product as it provides us with a cloud-native DB that provides MySQL and Postgres compatibility while simultaneously offering all the benefits of a cloud-native product - built-in security, continuous backups, serverless computing, and high integration with other AWS Services. It is ideal for powering a number of web applications based on the LAMP or LAPP stack.
  • Scale
  • Elasticity
  • Durability
  • Security
  • Opinionated in the way it does things
  • Tight AWS integration
Amazon Aurora is ideal for applications running in the well-known LAMP or LAPP stacks. It's generally great and the benefits of cloud-native elasticity, scale, security, ease to set up replicas and backups, and so on make it ideal for web-based applications. However, you need to be a tiny bit careful when using Aurora - and this is true for all products that generally emulate/simulate products. Generally, the more strange or exotic MySQL or Postgres features you are using, the more problems you're going to have with Aurora. However, as most LAMP/LAPP stacks aren't generally too exotic these tend to be edge cases that can be coded in other fashions.
Score 10 out of 10
Vetted Review
Verified User
Amazon Aurora offers a secure database for the functional requirement. The query system is very responsive and generates insightful metrics. The application has an efficient space management feature and is quite capable of storing big chunks of data. The feature is beneficial in instances where we need to take a backup of the entire drive and access data from a remote location.
  • Compatible with MySQL
  • Storage space management
  • Cross platform
  • Fail proof
  • The storage space is increased from 64 TiB to 128 but still, it is not enough for large organizations.
  • Compatibility issues with older MySQL.
  • MySQL features, like the MyISAM storage engine is missing.
Amazon Aurora is well suited for big organizations looking for a web-based -MySQL-linked cloud solution. The service is economical and offers a robust and dependable platform for storing big chunks of data. It provides fast database cloning and provides performance metrics, like query throughput and latency. With the older version of MySQL, it does not work properly.
Piyush Goel | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
We use Aurora as the de-facto DBaaS product for hosting our Relational Databases, primarily MySQL. We have over 100 MySQL clusters (Master, Slave) across the microservices and the 5 global regions where Capillary's SaaS products are hosted. Prior to Aurora, all our databases were self-managed and hosted on EC2 instances with EBS volumes, having provisioned IOPS, for storage. As our system scaled, the management of the databases became a full-time job. Also, configuration management, upgrades, and regular maintenance started eating into the team's bandwidth. Furthermore, the chances of human errors and the consequent outages increased with the increase in the number of MySQL set-ups. To address these concerns, in early 2020, we migrated all our MySQL clusters from EC2 to Aurora. The Aurora service hosts over 400 TB of data, and the Aurora instances vary from 4 cores, 32GB RAM to 32 cores, 256 GB RAM configs. The storage layer varies anywhere from 200GB to 30 TB. In a nutshell, all relational, OLTP use-cases for the 700M odd end-consumers touched by Capillary's platform and served out of Aurora.
  • Auto-expansion of the disks. The administrators don't have to worry about disk sizes anymore.
  • Default configuration sets are designed for the majority of the OLTP use-cases. As a developer, I don't have to worry about tuning the MySQL configurations anymore.
  • Better Performance than MySQL hosted on EC2 instances. The Aurora architecture allows faster replication as well.
  • Access to slow query, and error logs is a little cumbersome. Maybe, stream that to an AWS Elasticsearch, and provide searching out of the box (even if it means additional costs).
  • Upgrade to higher versions of MySQL is a problem.
  • Failovers to replica, although, they are not needed often, they can be made more seamless.
Well Suited: If you have to manage 10 or more MySQL clusters in your environments. Better to use Aurora and configure via a Terraform provider. Don't have to worry about the scalability of your databases. It scaled beautifully with tons of features that make the scaling process easier. Don't have a dedicated infrastructure team. Use the managed service, and let your developers focus on product development.

Less Appropriate: It can be a bit pricey. If you are operating under a budget, this may not be the right tool. RDS is slightly cheaper than Aurora. Configurations and documentation can be confusing at times, but if you have access to the AWS Solution Architects, it gets easier.
  • Online training
James Hilton | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Aurora is our SQL solution for users, events, articles, and more. Aurora provides convenient scaling and availability in different physical locations. The security and scaling are automated to support peaks in traffic and save money when it's quiet. The integration with other AWS services makes it convenient for us to use in all applications. The SQL language support made the migration from a dedicated MySQL server seamless in our codebase.
  • Automatic scaling of read replicas
  • Quick vertical scaling of server size
  • Scaling metrics to determine the right time to scale for cost efficiency
  • Better explanations of configuration settings
  • Easier error logging when failovers are required
  • More information on best practices for common scenarios like when database size gets too big or queries slow down
It is best suited when you need an easily manageable auto-scaling relational database cluster in different secure locations on Amazon Web Services and not best suited when you're not using Amazon Web Services or you are seeking a cheaper option for testing only or for low traffic sites, or you require a NoSQL database instead.
Arthur Zubarev | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User
Amazon Aurora has been chosen as a drop-in replacement for another popular, but a less affordable relational data storage engine. At time of this writing the system is getting ready to be commissioned in for production use on a select application basis. Given the adoption is, and it appears to be very positive, Amazon Aurora will be the sole choice for any other future implementations and serve as a replacement to other transactional databases. My personal view of what business problems Aurora solves or addresses well:
  • Aurora stands out in clustering (or multi-zone high availability) provided out of the box
  • DBA-less (almost) solution, at least the server-side aspect is muted, no patching or any hardening to make
  • Scale horizontally or vertically, or both.
  • The serverless option is attractive for ad-hoc use
  • Read-only replicas for robust analytics
  • Easy of programmability, supported by most drivers immediately
  • Easy scaling - can be either horizontal and/or vertical.
  • Nearly seamless backups, easy management.
  • 0 worries about server-side security.
  • Secondaries: up to 15 read-only replicas are enough even for very analytics hungry enterprises plus it makes all the data immutable.
  • Speed: it is hard to say 100% accurately, but in my view, Aurora beats all in the cost to speed ratio.
  • The Small and Medium instances are only good for testing or development, the number of connections and resources is limited.
  • The 5.7 as the latest version of AWS Aurora in MySQL compatibility is behind feature-wise to what the most recent release of MySQL offers (the same applies to Postgres mode).
  • Some odd or sub-optimal configuration values with some parameters not changeable.
  • No online development experience. So one must rely on Open Source tooling that is typically subpar to commercial offerings which in turn often are pricey and requires a desktop environment. I wish AWS Cloud 9 could offer in the Cloud Aurora development.
The pros:
  1. Completely DBA-less (or nearly so)
  2. Can replace most RDBMs
  3. Ideal for fast-growing companies or those that need to scale out and back. This is not so easy with say NoSQL or Hadoop-based products
  4. For most programmers or database developers, starting to code against MySQL is an easy thing, most mature programming languages have a native driver, MySQL shell
  5. Good enough for simple analytics as enterprise reporting, so it can forfeit the need for a dedicated data mart or even a data warehouse
The cons:
  1. Can be ~ 20% costlier than just a self-managed MySQL instance
  2. Outdated version-wise compared to where Oracle's MySQL is
  3. As a result of the older version used some analytical functionality is beyond reach for ordinary developers or analysts or requires the use of mature commercial tools
The support as a whole cannot be applied to just Aurora, but I must say that the response to our tickets from the AWS side was a bit anemic. Despite that, there is plenty of documentation and forum articles that should make anybody self-serviced. Again, let me stress this out - the product (in either MySQL or Postgres form) was used by many people and thus now well understood, explained and there are plenty of books and other material available. This is not the case that we encountered with NoSQL.
Michael Jenkins | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
Many teams at my company use Amazon Aurora for database provisioning and management. In my teams case, we rely on the "out of the box" capabilities of Aurora to give us open-source compatible databases that are highly available, fault tolerant, and self healing. The main problem that Aurora helps us address is minimizing the amount of time and effort we spend on deploying and managing our database infrastructure in addition to the data stored there.
  • High availability
  • Fault tolerance
  • Back up and restore
  • Open source database compatibility
  • Pricing: indeed there is a premium for using Aurora but the cost is worth the benefit of minimizing the time spent tending database infrastructure.
Aurora is great for situations where databases require autoscaling and need high availability. For example, high traffic websites running on an autoscaling compute layer can benefit by being connected to a datastore that can scale along with them. Also any scenario that requires fault tolerance can benefit greatly from Aurora. Knowing that your DB can heal itself (to the best of its ability) can give developers and engineers confidence that their application will handle adverse scenarios in the event of failure conditions. Given the premium of running DBs with Aurora, I would not recommend using it for development environments. Given that Aurora is compatible with most common DB software, development environments can use cheaper, smaller RDS instances. When it comes time for deploying into a production environment, no changes would be needed.
AWS has been top notch in providing support for Aurora and RDS as a whole. For the most part, there is rarely ever a need to request support for our database deployments. The only interactions I can think of off hand are asking for increases in the number of instances we can deploy.
Ilyas Bakouch | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Amazon Aurora is widely used by multiple teams in the organization essentially for two reasons: its high throughput in comparison with standard MySql and its S3 real-time, continuous backups.
  • Optimized storage type for intensive I/O operations.
  • Continuous backups to S3.
  • 5x higher throughput than regular MySql 5.6.
  • Even though you are only billed per second of usage, there is a minimum of 5 minutes billed each time the database is active.
  • For high load apps, Aurora Serverless is extremely expensive as compared to a single provisioned Aurora instance.
It's not obvious to plan database capacity for a year out, so I usually avoid buying reserved instances. However, the ability to buy “Reserved ACUs” would be something interesting concept. That way you could prepay for hours of capacity at a discounted rate. If your load is stable but peaks at certain times, go for an Aurora Serverless, it will be way cheaper than reserved instances.
I never had issues with Aurora that forced me to deal with support. It has been stable and reliable so far, at least in my experience and my team's.
Score 10 out of 10
Vetted Review
Verified User
We use it as our primary data store for customer data. It allows us to handle our large traffic load during peak hours. We use a variable number of reader nodes depending on traffic.
  • Adding and removing reader nodes is seamless
  • Failover is fast
  • Low replication delay on reader nodes
  • Some quirks exist with corner case behaviors. e.g. we had some perf issues with GIN indexes.
  • A little slow to provide the latest Postgres versions. We'd love to use Postgres 12.
  • The endpoints are ok, but we end up implementing our own to better meet our use cases.
  • Best practices incur additional data transfer costs. I would expect those not to be charged.
Variable read load. Being able to autoscale your DB is amazing. Operationally, not worrying about failover is also amazing. Outside of Aurora/RDS, Postgres failover is always a big pain. Even on plain RDS, there's some concern with data loss in a failover.
We've hit a number of known bugs and have to wait for a minor release to get them fixed. We've also hit some reproducible bugs and we're met with a lot of resistance from support as we shared them.
Score 10 out of 10
Vetted Review
Verified User
Amazon Aurora is essentially a relational database as a service on AWS. Since it is cloud-based, there are many advantages to its name. First of all, it is a server-less database which essentially means that you do not need to host a physical server and provide space for it. Secondly, it is a pay-per-use model which means you only pay whenever you use it, which is a great feature if you do not make everyday queries into the database. Since it is again an amazing product from Amazon, it fits very well in the AWS ecosystem. You can use it to scale your database as per your needs, no need to buy server space and resources in advance, then not use them. It can scale and descale according to your needs.
  • It is a high performance and low latency database. You can also be assured of the high-availability of the database and the services hosted.
  • The Security provided by Amazon is again top notch because all of the data is encrypted and secured. The customers feel much more relaxed and assured when the project is using Amazon Aurora to host their services.
  • A big plus point for Amazon Aurora is the latest and impactful upgrades which it brings in the package. The automated up-gradation and maintenance is an outstanding feature which it provides to receive and stay up to date with the latest upgrades in the DB world.
  • It is compatible with MySQL and PostgreSQL. It essentially means that the database is able to support the old data-sets and tools which were being used on those DB's. This is a great advantage because it is essentially backward compatible.
  • The Amazon technical team behind the development of this software is very knowledgeable and supportive as well. We told our requirements clearly and they suggested the best use of the database for us, which scenario it should be used, and which it is not a perfect fit.
  • I think the biggest point for a project or team to consider is the cost. Although it can scale and descale according to your requirements, still you need to be cautious and have a vision of how big your database is going to be, how complex it is going to be, and how much does latency matter. You need to factor all those decisions before going to spend extra on Amazon Aurora as compared to a simple MySQL database.
  • It suffers from Clod start which is a very well known aspect of the product. But the recovery part is also not up to the mark. They need to improve on the ability to restore a copy of the backup, but mostly it is seen that the copy is corrupted or not the latest one.
  • It does allow us to add new nodes to the existing cluster but we need to be wary of that the new nodes are read-only nodes. All the functions of write/update will still be carried out by the master node only.
Amazon Aurora is best suited for creating complex, highly available and commercial databases, in a very straightforward way. The database size should be medium to large because only then will you be able to justify the extra cost incurred for using Amazon Aurora. Another aspect is that if you are already using AWS and most of your applications and services are on the cloud, then it makes sense to use Amazon Aurora since it fits in the Amazon ecosystem really well.
Jesse Bickel, MS - PMP | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Our organization has a need to store massive amounts of logs in AWS S3 storage. We use Amazon Aurora to query against that data and avoid using high priced third-party logging indexing software and their hot storage. AWS Athena use is isolated to our development teams and business analysts only. The main purpose for our organization using Amazon Aurora is simply cost savings and further centralizing under the AWS platform.
  • Amazon Aurora's billing style is ideal. You only pay for what and when you use it. If you store large amounts of data but do not need to query against it, there is no cost until you do.
  • Amazon Aurora is highly supported and has seemed to be supported by a knowledgeable staff. While the use rolled into our premium support agreement, we found their staff and training resources to be well above average.
  • The speed is industry leading relational database. That simple. Faster, more secure and reliable.
  • While the service is outstanding there does seem to be a routine issue in connecting or keeping connections to Amazon RDS DB Instances at times or the connection is slow. I think clearer documentation would be highly beneficial here.
  • Increased logs or discovery notes in the event of a replication failure.
Amazon Aurora is an ideal and industry-leading storage subsystem that allows you to manage costs utilizing the data but also accessing the data with incredible speed. The database engine seems to really leverage the benefits of Amazon's distributed storage and scaling of that storage. Aurora eliminated numerous manual processes and reduces operational overhead in processing & replication. Depending on how often and quickly you need access to those databases will determine if this is a fit for your organization. If you need constant hot storage and access full time this is not ideal. If you can tolerate the process of a query than this is highly effective.
March 11, 2019

Amazon Aurora Review

Score 9 out of 10
Vetted Review
Verified User
Amazon Aurora is a PaaS database product from AWS that is a drop-in replacement for existing workloads utilizing either a MySQL or PostgreSQL backend that improves upon the database engine performance of those open source projects. We leverage Aurora for its simple scaling without having to take a cluster down, and find its auto-scaling storage to be a better fit for our workloads than having to guess ahead of time and over-provision.
  • Performance: We utilize Aurora as a PostgreSQL replacement, and Aurora's throughput is up to 3 times higher.
  • Simple Instance Auto-Scaling: We can scale the underlying database engine up or down with no down time.
  • Auto-Growing Storage: Rather than having to over-provision, Aurora automatically adds blocks of 10GB to your storage cluster up to multiple terabytes of storage.
  • Support for additional engines: Right now, Aurora is limited to MySQL and PostgreSQL.
  • PostgreSQL-specific Instance Types: The PostgreSQL has high minimum instance type variants; while MySQL can take advantage of t3 instances, the minimum PostgreSQL instance is too large for lower-budget workflows and tests/debugging.
For workloads that already use, or plan on using, MySQL or PostgreSQL, Aurora is our new go-to favorite deployment option for projects on AWS. The best use cases for Aurora will be substantial workloads that are well-suited to the simple scaling controls (both from an instance type perspective, as well as storage perspective), and will benefit from Aurora's simple, very low latency read replicas. Aurora is extremely fault tolerant and has improved self-healing ability.
Score 9 out of 10
Vetted Review
Verified User
Amazon Aurora is a relational database as a service which supports MySQL and Postgres DBs on AWS.
My organization uses a lot of serverless features on AWS for developing microservices. In this regard, we use AWS Lambda for microservices and Amazon Aurora for a relational database.

This is a lightweight maintenance-less option of providing microservices without having to maintain the infrastructure including AMI rehydrations on AWS.
  • Aurora is a relational database as a service on AWS which is MySQL and Postgres compatible. So if you are looking for a serverless option which going through need to host and manage a database then Aurora as a service is great.
  • It is a simple and cost-effective open source database which is much cheaper than a normal database cost. Hence very efficient for microservices database where you do not need one very large centralized database but many small databases that are available and low latency.
  • Aurora provides high performance and low latency. Last year they also announced multi-master in the same region and read replicas in multiple regions. This is very convenient if you are trying to design and build a highly reliable application.
  • Just like AWS DynamoDB which is a not a SQL solution and is truly a global DB, it would be great if AWS Aurora can become a global DB. What that means is that it is multi-region multi-master. That way writes to different regions of AWS would all be in sync and available in replicas on different regions.
Many places where Aurora is well suited:

  • If you are trying to build a serverless backend.
  • Amazon hosted relational database service (RDS). So we do not have to manage the database maintenance.
  • Backup and archival can be done to AWS S3, which is very convenient.
  • It provides high performance and scalability.
  • It's very secure. You could use AWS Key management service (KMS) to encrypt and store data on AWS Aurora.
Score 9 out of 10
Vetted Review
Verified User
The engineering team uses Amazon Aurora Serverless to rapidly build services that are inexpensive to operate and maintain. Aurora Serverless is an ideal datastore for low-volume or bursty services that can tolerate its cold starts; services consumed by batch jobs are an example. Amazon Aurora Serverless is a fast MySQL 5.6-compatible datastore; it helps our small team because it is managed and very inexpensive.
  • Aurora's throughput is great compared to MySQL and MariaDB.
  • Aurora Serverless's pay-per-use makes it very inexpensive when used for services that are idle most of the day. This helps us adhere to the one-database-per-microservice pattern; cost is no longer a concern.
  • Aurora is mostly managed. Administering databases will never be a competitive advantage for my company.
  • Aurora has great integration with other AWS products, like DMS.
  • Cold-starts are part of the Aurora Serverless compromise, but they are painful nonetheless.
  • We're accustomed to sub-second metering for AWS Lambda; Aurora Serverless has 1-minute minimums for resources.
  • Aurora Serverless is compatible with MySQL 5.6. MySQL 5.6 lacks many of the features PostgreSQL users will expect.
Amazon Aurora Serverless is great for micro-services and serverless. If DynamoDB's pricing structure and management appeal to you, but you want a RDBMS, consider Amazon Aurora Serverless. If you have a microservices architecture and are apprehensive about the cost of one-RDS-instance-per-service for every test cluster, consider Amazon Aurora Serverless. Aurora MySQL lacks many features you'd expect from PostgreSQL; the absence of these features may be more tolerable for OLTP use-cases than OLAP use-cases.
Score 9 out of 10
Vetted Review
Verified User
I use Amazon Aurora as a relational database in the cloud in the aws eco-system mainly as a SQL data-store for transaction analytics. Find it really superior for its sheer faster performance as a relational data base - much faster than a traditional RDBMS data base and is much cheaper than some its competitors. It is offered as 'database as a service' and hence the worries of finding hardware to provision is not there and can get quickly started.
  • used as a supplement to mySQL database in the business for SQL
  • sheer power of performance is much faster
  • supports data growth/data storage and having replicas of databases very well
  • ability to read faster from the replicas in the event that there is a problem with Amazon Aurora - there is a latency involved and this can be reduced
  • supports only a particular version of mySQl 5.16.10 and hence does not work with older versions
It works very well with mySQL and can supplement it very nicely with much faster performance and its ability to scale up as well as replicate data across multiple clusters. In addition it is very well suited for large workloads of an enterprise that is looking to get up and running quickly on a managed RDBMS service without worrying about licenses/provisioning and the like.
Andrew Raines | TrustRadius Reviewer
Score 10 out of 10
Vetted Review
Verified User
We use Amazon Aurora as our primary data store which underlies the bulk of our system operations - primarily via web APIs. Its used beneath a PHP stack as a MySQL compatible cluster in a master-slave configuration. We also have master-only clusters for our development and test environments.
  • The MySQL compatibility meant we didn't have to change anything in our system which used to run on a MySQL database. It was a very simple configuration change to point at the new instance once set up
  • Much better performance than our previous MySQL database (hosted on AWS RDS) for lower costs due to the way storage is managed
  • Storage management is much more simple as it grows and shrinks with you without having to allocate and deallocate storage to the database
  • Without direct access to the instances it isn't possible to do a few things you'd be able to do if you were running your own database server, but this is rarely an issue
When already using a relational database, either MySQL or PostgreSQL, the change to Amazon Aurora should be very straightforward. The main benefits you get are cost efficiency and ease with regards to the storage, as it scales with you, and managing clusters including failovers are made very straightforward for you.

If you are looking for a database which can scale up and down quickly with demand, Aurora may not be the best fit. However, there is now an Amazon Aurora Serverless service which attempts to address this requirement. I do not have any experience with it, so cannot comment further - but it is possible it will fit your use-case.
Vasco Mendes | TrustRadius Reviewer
Score 8 out of 10
Vetted Review
Verified User
Cloud services are the trend. No infrastructure costs and no worries. Cloud databases are also the trend, as they can be easily scalable and upgraded.

As a senior consultant I recently configured an Amazon Aurora database to serve as the back-end of an organization software. This software included a main server providing services for mobile applications and also as a back-office web application to manage transaction information. These services relied on the Amazon Aurora database to collect and save information. Customer needed a database accessible from everywhere, with high availability, fast, always up to date and scalable as it was expected the business to grow as well as its storage needs. The Amazon Aurora turned out to be a stable solution with high performance when compared with in-house solutions like MySQL.
  • Amazon Aurora has high availability, since the customer started to use it, the database never had to be left out of service.
  • Amazon Aurora provides frequent and automated upgrades, which makes our database system always up to date on the latest features and security practices
  • Since Amazon Aurora uses MySQL as its core database, it is very easy to find specialized people to work. Amazon’s relational database management system also makes it very easy to expand and create new databases
  • The cost of Amazon Aurora when compared to a simple MySQL instance is considerably higher, so we really need to look at and run some performance tests to compare if the performance improvements are worth the extra cost.
  • Although backup restores are a rare feature to use, when we need them it is always painful to restore our data. We are always searching for a database service to provide new and innovating features in terms of data recovery. For instance, being able to search on backup information to see if the needed data is there. It is a very common need to compare the hot data with the backup data, for example to fix some database data that a malfunction application wrongly updated.
  • Since aurora is an Amazon relational database service there is no way to run a dev database on a local storage for tests and development.
Amazon Aurora should be considered for those who need a fast and reliable cloud database service. It includes the main features of a MySQL database, using the latest trends in architectural principals. It ensures out-of-the-box fault-tolerance and high scalability. It is also very important for those who don’t want to worry about features and security updates. As the price is higher than a standard MySQL for instance, it should only be considered for higher applications where performance and scalability is really important.
Score 7 out of 10
Vetted Review
Verified User
Amazon Aurora is used by my organization as the backend for our software. Previously, we hosted our own MySQL servers which inevitably due to lack of resources ran behind on updates and thus performed more poorly than it should. Moving to Amazon Aurora has improved performance for a database that was poorly designed at the start and was operating on a slowly outdated MySQL version. Moving to Amazon Aurora not only improved performance, but allows my company to continue with fewer resources but yet have the advantage of a database that is more stable and stays up to date with the latest features. Since moving to Amazon Aurora, we also have fewer replication errors since Aurora does this flawlessly.
  • Automated maintenance for upgrades is by far the most superior feature of Amazon Aurora. Never be behind on upgrades again!
  • Performance improvements for poorly structured schema due to enhancements added by Amazon.
  • Replication works flawlessly due to added security measures added into Amazon Aurora which prevents admin users from "accidentally" breaking the slave instance.
  • Amazon Aurora is hosted on Amazon's RDBMS which also includes quick and easy setup of new database instances.
  • I'd like to see Amazon Aurora get ahead of the curve on MySQL and introduce their own improvements to MySQL to make it a superior database so that I don't need to use SQL Server or Oracle to get performance improvements. For example, improve performance of views.
  • Amazon Aurora needs to improve the ability to restore backups as needed. Currently, the user can only restore an entire instance to a new or existing RDBMS instance. If you need to retrieve data from a single table, this can be tedious after waiting hours for an entire restore to complete. Instead, allow the user to select a database to restore. Better yet, allow the user to restore a database backup to ANOTHER database - which would allow you to restore a database on the same instance.
  • Again beat MySQL to the punch and introduce REAL server to server communication since they have disabled the "Federated Engine" which was the only way previously to do this. I'd like to be able to setup MySQL instances to talk to other MySQL instances.
Amazon Aurora (as is MySQL) is better suited for light to medium applications considering it still has some performance limitations from MySQL. I would not recommend it for enterprise level use without a carefully constructed backend system (code and database). My company's current backend architecture was not mapped out very well and this leads to performance problems that even Amazon Aurora has not been able to completely sort (although it has been a huge help).

Another area where I am finding it beginning to lack is for use in data warehousing. The more rows added, the less performant I'm finding the data warehouse. Although to be fair, Amazon has another product (Redshift) that we are looking to migrate data warehouses into.
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