Filter Ratings and Reviews
Filter 65 vetted Amazon Aurora reviews and ratings
Reviews (1-12 of 12)
November 11, 2019
Extremely handy, well integrated and easy to use
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.
October 04, 2019
Old Database New Again: AWS Aurora, and it Shines
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.
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.
August 07, 2019
Amazon Aurora is the database to lookout for in the future
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.
October 18, 2019
Very happy with Aurora, especially operationally.
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.
December 14, 2018
great RDBMS that can scale up and replicate very well
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
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.
February 08, 2019
Amazon's opensource relational database service
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.
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.
January 17, 2019
A Serverless Future for a Database from the Past
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 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.
April 20, 2018
Great performance and easy transition from MySQL
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.
- 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
October 26, 2017
Amazon Aurora - A Boost on Standard MySQL
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.
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 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.
- 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.
Amazon Aurora Scorecard Summary
About Amazon Aurora
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.
Categories: Database-as-a-Service (DBaaS), Relational Databases
Amazon Aurora Screenshots
Amazon Aurora Videos (2)
Amazon Aurora Supported Products
AWS Lambda, Amazon Relational Database Service (RDS), Amazon Elastic Compute Cloud (EC2), Amazon S3 (Simple Storage Service), Amazon Simple Notification Service (SNS), Amazon RDS Data API
Amazon Aurora Competitors
Pricing
Amazon Aurora Support Options
| Free Version | Paid Version | |
|---|---|---|
| Forum/Community | ||
| FAQ/Knowledgebase | ||
| Social Media | ||
| Video Tutorials / Webinar | ||
| Phone |
Amazon Aurora Availability
| Geography: | NAMER, EMEA, APAC, LATAM |
|---|---|
| Supported Languages: | English, French, Chinese, Korean, Japanese |