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Updated on: August 15, 2020
What is Amazon Aurora ?
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Amazon Aurora

MySQL and PostgreSQL-compatible relational database
(12 Ratings) Write Review

Amazon Aurora is a MySQL and PostgreSQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides multiple levels of security for your database. These include network isolation using Amazon VPC, encryption at rest using keys you create and control through AWS Key Management Service (KMS) and encryption of data in transit using SSL. MySQL and PostgreSQL compatibility make Amazon Aurora a compelling target for database migrations to the cloud.

Amazon Aurora Features Show All Features

Amazon Aurora Technical details

Support 24/7 (Live rep) Customer Type Large Enterprises Medium Business Small Business
API NA Location / Phone Number Seattle, Washington
Deployment SaaS/Web/Cloud Category Database Management Software

Amazon Aurora Pricing

Pricing ModelSubscription
Amazon Aurora
$0.04

Database Instances

  • $0.041 Price Per Hour for db.t3.small (Standard Instances - Current Generation)
  • $0.082 Price Per Hour for db.t3.medium (Standard Instances - Current Generation)
  • $0.29 Price Per Hour for db.r5.large (Memory Optimized Instances - Current Generation)
  • $0.58 Price Per Hour for db.r5.xlarge (Memory Optimized Instances - Current Generation)
  • $1.16 Price Per Hour for db.r5.2xlarge (Memory Optimized Instances - Current Generation)
  • $2.32 Price Per Hour for db.r5.4xlarge (Memory Optimized Instances - Current Generation)
  • $4.64 Price Per Hour for db.r5.8xlarge (Memory Optimized Instances - Current Generation)
  • $6.96 Price Per Hour for db.r5.12xlarge (Memory Optimized Instances - Current Generation)
  • $9.28 Price Per Hour for db.r5.16xlarge (Memory Optimized Instances - Current Generation)
  • $13.92 Price Per Hour for db.r5.24xlarge (Memory Optimized Instances - Current Generation)

Database Storage and IOs

  • Storage Rate: $0.10 per GB-month
  • I/O Rate: $0.20 per 1 million requests

Backup Storage

  • Backup Storage: $0.021 per GB-month

Backtrack

  • Change Records: $0.012 per hour 1 million Change Records

Snapshot Export

  • Charge per GB of snapshot-size: $0.010

Data Transfer

  • All data transfer in: $0.00 per GB
  • Up to 1 GB / Month: $0.00 per GB
  • Next 9.999 TB / Month: $0.09 per GB
  • Next 40 TB / Month: $0.085 per GB
  • Next 100 TB / Month: $0.07 per GB
  • Greater than 150 TB / Month: $0.05 per GB

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Disclaimer: The pricing details were last updated on 01/08/2020 from the vendor website and may be different from actual. Please confirm with the vendor website before purchasing.

Amazon Aurora FAQs

Amazon Aurora is Database Management Software. Amazon Aurora offers the following functionalities:

  • Backup
  • Data Migration
  • Data Replication
  • Database Conversion
  • Monitoring
  • Performance Analysis
  • Queries
  • Relational Interface

Learn more about Amazon Aurora features.

The pricing for Amazon Aurora starts at $0.04. Amazon Aurora has a single plan:

No, Amazon Aurora does not offer a free plan.

Learn more about Amazon Aurora pricing.

No, Amazon Aurora does not provide API.

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Amazon Aurora Reviews

OVERALL RATING
4.5
Based on 12 Rating(s)
Rating Distribution
  • 11
  • 1
  • 0
  • 0
  • 0
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Verified UserSource : trustradius.com
(Reviewed on 18 October 2019)
Very happy with Aurora, especially operationally.

Use Cases and Deployment Scope

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.

Pros and Cons

  • Adding and removing reader nodes is seamless
  • Failover is fast
  • Low replication delay on reader nodes
Edit
  • 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.

Likelihood to Recommend

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.
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Arthur ZubarevSource : trustradius.com
(Reviewed on 04 October 2019)
Old Database New Again: AWS Aurora, and it Shines

Use Cases and Deployment Scope

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

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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
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Verified UserSource : trustradius.com
(Reviewed on 07 August 2019)
Amazon Aurora is the database to lookout for in the future

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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.
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Andrew RainesSource : trustradius.com
(Reviewed on 20 April 2018)
Great performance and easy transition from MySQL

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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
Edit
  • 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

Likelihood to Recommend

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.
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Jesse Bickel, MS - PMPSource : trustradius.com
(Reviewed on 21 June 2019)
High-Speed, Low-Cost and logins for years. Amazon Aurora filled a huge need!

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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.
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Verified UserSource : trustradius.com
(Reviewed on 11 March 2019)
Amazon Aurora Review

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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.
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Verified UserSource : trustradius.com
(Reviewed on 08 February 2019)
Amazon's opensource relational database service

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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.
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Verified UserSource : trustradius.com
(Reviewed on 17 January 2019)
A Serverless Future for a Database from the Past

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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.
Edit
  • 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.

Likelihood to Recommend

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.
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Shiv ShivakumarSource : trustradius.com
(Reviewed on 14 December 2018)
great RDBMS that can scale up and replicate very well

Use Cases and Deployment Scope

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.

Pros and Cons

  • 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
Edit
  • 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

Likelihood to Recommend

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.
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Ilyas BakouchSource : trustradius.com
(Reviewed on 11 November 2019)
Extremely handy, well integrated and easy to use

Use Cases and Deployment Scope

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.

Pros and Cons

  • Optimized storage type for intensive I/O operations.
  • Continuous backups to S3.
  • 5x higher throughput than regular MySql 5.6.
Edit
  • 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.

Likelihood to Recommend

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.
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Videos on Amazon Aurora

Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS
Introduction to Amazon Aurora - Relational Database Built for the Cloud - AWS
AWS re:Invent 2018: [REPEAT 1] Deep Dive on Amazon Aurora with MySQL Compatibility (DAT304-R1)
Achieve Database Freedom with Amazon Aurora

Amazon Aurora Screenshots

Aurora MySQL Connect
Aurora Create Custom Endpoint
Restore DB
Aurora MySQL Connect
Aurora MySQL Connect
Aurora Create Custom Endpoint
Restore DB

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