Amazon Aurora Pricing Overview

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What is Amazon Aurora?

Amazon Aurora is a global-scale relational database service built for the cloud with full MySQL and PostgreSQL compatibility.

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Aurora Pricing 2021

Large companies generate large amounts of data. From projects to employee information, business account details, and more. Many of that data is relational, meaning that you may need to connect individual employees to their business accounts, and to their work performance records.


Databases like this are called relational databases and are generally coded with SQL. One major developer of relational databases services is Amazon Web Services. AWS Aurora is their managed SQL database option. Instead of managing the upkeep of the database, you leave it to an almost completely self-sufficient system.


If you already know about Aurora then feel free to go straight to the pricing explanation. If you may be unfamiliar with what exactly Aurora is continue. At the end of the article, there is a key terms breakdown of all developer and database terms used.


For a quick preview of Aurora, there is Amazon’s demo video for the product.

What is AWS Aurora?

Aurora is a relational database service for MySQL and PostgreSQL. AWS claims to have both the simplicity of an open-source database and the dependable quality of a commercial database.


Amazon reassures users with existing databases that the transition will not force them to make drastic changes to their code. They even note that depending on the company’s workloads, they can deliver around 5x the throughput of regular open-source MySQL, and 3x the throughput of PostgreSQL.


That’s not to say using the open-source SQL databases MySQL and PostgreSQL is inefficient. MySQL and PostgreSQL are worthwhile databases for large, and incredible projects. If you are an individual, private team, or a new startup, using open source databases is a great choice. These tools are often lacking in the polish and integration capabilities of vendor-sourced options.


When it comes to larger companies or teams, it’s can be easier to streamline the upkeep and use a service with valuable integrations, without having to put too much manual work into it. Unfortunately, the price tag on those kinds of services can be a big strain on certain budgets.

How Much Does AWS Aurora Cost?

AWS Aurora pricing has no upfront fees. They base their monthly fees on your usage of their services. Figuring out usage costs can be difficult because even with the pricing calculator there may be differences in the estimate. The pricing options have their own options so it can be a mathematical minefield to navigate. As a result, it is best to have some wiggle room in your budget initially to compensate for the unclear costs you may incur.


AWS explains that your storage is billed by GB-month increments or just the amount of storage per month. Input/output (I/O), is billed by the number of requests in, increments of a million. There can be extra charges if you use their Global database, Backtrack, Snapshot Export, or transfer any data from your Aurora database.


There are several different costs based on the type of PostgreSQL or MySQL database you use. The versions Amazon provides prices for are the MySQL and PostgreSQL-compatible editions with Aurora. These costs have a wide range depending on the type of instance.


For MySQL compatible editions, the range for a standard instance is $0.073-$0.164 per hour. For a Memory-optimized instance, it can be $0.377-$13.92 per hour. Your chosen region will also change the costs. These prices were taken from the default US East (Ohio).


Amazon also has separate pricing for On-Demand and Reserved pertaining to your chosen edition of MySQL and PostgreSQL. On-Demand pricing is offered for Amazon Aurora Serverless, where your database capacity regulates itself. For this configuration, you would pay for capacity, storage, I/O. You would not pay for when the database is not in use, but the capacity costs are measured in seconds. The capacity of your database is measured with ACU, or Aurora Capacity Units.


Reserved instance pricing would be if you preferred more committed, set costs. Ideally for databases that will be used for a very clear, predictable amount of time. You pay an upfront cost on the subscription and then are discounted hourly costs. You will be charged regardless of how much you use, and need to commit to 1 year or more.


The standard 1-year term for reserved pricing has $0 to $243 in upfront fees. The more you pay upfront, the less you pay hourly, and the higher the discount you will receive compared to the on-demand hourly rate. For stable companies with guaranteed needs and the capital to do so, paying up front is a great way to save money.


To provide you with a more visual understanding of how much your database could cost, we talk about the pricing calculator next.

AWS Aurora Pricing Calculator

The costs calculated from AWS’ pricing calculator should be really considered as a ballpark estimate. For the estimate, we kept most of the defaults. This way your ballpark figure is closer to the bare minimum. For a unique number, we recommend you enter your current database information or your expected information.


There are quite a few input options when setting up your database. For starters, they separate the pricing between MySQL and PostgreSQL when you’re choosing which service to add to your calculator estimate.


We chose PostgreSQL on-demand pricing. All of the other information entered was the default for a one instance database.


The math formula they use to get the pricing is as follows: 1 instance(s) x 9.28 USD hourly (for the type of database) x 730 hours in a month = 6774.4000 USD which ends at the estimate of $6,774.40 each month.



If you want to see this better or play around with your own pricing you can go here.

How Does AWS Aurora Work?

Aurora is meant to not only be a managed database but it’s also meant to be reliable storage. The database is structured for backup and disaster recovery. The storage is designed to manage itself, and be sufficient in optimizing enough space for all your data, records, and any kind of information.


AWS’ explanation for how Aurora can do this is their separate, cloud-based service that exists to make relational databases easy to run, grow, and use.


Aurora is connected to Amazon Relational Database Service Amazon RDS. RDS is part of why Aurora is good for managing your MySQL or PostgreSQL database. The web service allows you to use Aurora as a DB engine while setting up your server.


Aurora then accesses the RDS management console, AWS CLI, and APIs, and uses them to perform major database care. These include but are not limited to provisioning, backup, failure detection, repair, and recovery.


Through RDS, Aurora is less reliant on single database instances and uses DB clusters instead. With multiple database servers, they replicate and manage the storage of your data. This will then make it easier for daily operations and auto-scaling.


For more about the type of system, Aurora is, how the storage relates its speed, and how much cluster volume and other information about Aurora see Amazon’s full explanation.


AWS Aurora is a great option for its features and capabilities, but you may not be sure about committing. Below we talk about popular competitors that make pretty good alternatives. We also talk more about the open-source tools mentioned earlier.

AWS Aurora vs Google Cloud SQL vs Microsoft Azure

The three giants for managed SQL databases include AWS Aurora, Google Cloud SQL, and Microsoft Azure. They all have very similar pricing models and offer pricing calculators. One may seem less than another, but the reality is the cost depends on your unique database. In general, all of them can go into the thousands per month for usage of your SQL database.


Each of these services is suitable for major companies and is meant to manage large quantities of data. All of them have auto-scaling, multiple applications within their cloud, and are compatible with either MySQL, PostgreSQL, or SQL Server.


Microsoft Azure has compatibility with SQL Server, which is their own SQL service, along with PostgreSQL, and MySQL. Google Cloud SQL is compatible with the same, and also offers a NoSQL service for non-relational databases with their service Datastore.


Google is your best bet for organizing and accessing your data in several formats and database structures, . If you prefer SQL Server, the company that created it is probably best, so Azure is your better choice. Amazon RDS does offer DB engine options for SQL Server, but not with Aurora.


Other applications can also be an important factor for your use case, not just database structure.


AWS comes with a vast range of applications from machine learning, robotics, and business services. When you create or switch your database to Aurora you can access a number of services to benefit your code, company, and team.


Google Cloud comes with a number of applications for optimizing your projects and data. The options are fairly diverse with data warehouses and libraries to API and AI creation, with an array of developer tools available.


Microsoft Azure also has AI, machine learning, analytics, and developer tools. They have quite a few free services as well (that stay free after the first free 12 months of your account). These services include Visual Studio Code, Machine Learning, and DevTest Labs.


All three giants in development and data are great options to store and manipulate your relational database. One issue for some lower-budget teams is the cost of these giants. In the next section, we give a quick mention of the open-source SQL databases.


Most of these databases will require you manually manage them, so they are not the ideal option if saving save time and effort is a major priority. Fortunately, some of these alternatives do offer a managed version (but not guaranteed to be completely open-source).

Open Source SQL Online Databases

For those that aren’t familiar with the open-source options for SQL databases here we go over a list of the most common ones readily available. Some of these services will include a managed version and NoSQL options.


  • MySQL Databases

  • PostgreSQL Databases

  • SQL Server Databases

  • MariaDB Server Databases


MySQL may be the most popular and easy-to-learn database system. MySQL Community Edition is open source and ready for download. It’s compatible with NoSQL, meaning you can combine your nonrelational and relational data in the same place.


There’s also MySQL Enterprise Edition, which is a managed database with security, backup, encryption, and integrations. Enterprise Edition is not open for download and requires an Oracle account.


PostgreSQL is an open-source option ready for download. There most recent versions include 14.1, and 13.5. Their two new releases have heightened security and are highly recommended.


Microsoft SQL Server offers downloads for their free, open-source versions, SQL Server 2019 Developer, and SQL Server Express. You can also sign up for a Microsoft account and use SQL Server on the cloud.


MariaDB is from the creators of MySQL. You can see the common theme with the dolphin for MySQL, and seal for MariaDB. They have multiple downloads from as recent as November 2021. The new versions have advanced clustering and can be integrated with Oracle like MySQL.


For more information and resources see the next section. At the end of the article, we also provide a key terms list as well.

More Resources

Not everyone finds their needs with the most popular software in the field. You may want to shop around more. We have a list of managed database platforms. If you are also interested in NoSQL databases and learning more about Amazon’s RDS, you can see this video comparing AWS Aurora and AWS DynamoDB (Amazon’s NoSQL managed database).


If you have used any of the following SQL managed and unmanaged databases in the article, please consider leaving a review to help other buyers and developers.

AWS Aurora Key Terms Breakdown

Some of the terms and concepts you will see while shopping for a good relational database software might be new or require some review. Here we keep all the undefined phrases from the article, and extra explanations to give a good background to SQL databases.

SQL or Secure Query Language

SQL stands for Secure Query Language (SQL can be pronounced ‘Sequel’). It is a programming language for relational databases. With a relational database, you often connect specific parts of data to their related categories and information.


This can be for an employee who needs to be connected to their address information, hiring information, and performance review. It can also be for a client that you need to connect to their address, their company and company address, their specific client information, and any other categories they belong in.


You can then use those tables of information to research your own data or to pull the information you need to use. Using queries, you can take data from the tables of information, so you can have a custom view to organize your information.


You use a query to create a mailing list of companies you worked with in the past year so you can send out a newsletter to advertise some deals and changes to bring them back in. Relational databases make it easier to access the companies, the dates, and the addresses for the query. SQL is simply the language used to ask your database for things you want.


There are database systems that let you do this without learning SQL. Microsoft Access works the same way but it comes with a UI that lets you drag and drop instead of coding. If you are a small business this may be your ideal solution, but Microsoft Access is far too small for major projects or personal data of large companies.

NoSQL or Non-SQL or Non-relational Database

NoSQL is a newer coding language and is for non-relational databases. This could be storing information that you do not need to connect to several other categories. It could also be because you want to access the data in a different manner. NoSQL can be faster while handling large amounts of data, but without being impeded by complex structures found in SQL.


This does not automatically mean you can use a NoSQL database or SQL interchangeably. Not all information can easily be switched back and forth, because what you want in a relational database may not work in a NoSQL database.


When you can, however, switch to NoSQL it might be the better decision to access, analyze and use your data faster. Sometimes, NoSQL databases are cheaper, but not always. Even better, is in the cases where you can combine NoSQL data and SQL data in the same database so you can have both. MySQL has open-source versions that offer this capability.


If you are interested in changing to NoSQL see this article about the enterprise benefits to NoSQL.

VM Virtual Machine

A virtual machine is a simulation on a computer that lets you experience and test different operating systems or devices. This way applications can be designed for Mac and Windows, mobile apps for iOS and Android, and games for both Xbox and Playstation.


Those looking for virtual machine software can check out this blog post to explore some free options

Open Source / Open-source (hyphen is not required)

Open-source usually refers to software that is free to download, use, or study on the internet. The developer will make their license for the specific version that is free, open to be manipulated, used, distributed by anyone.


The reason someone would choose to not have a capital gain is because they want more developers to learn and create in collaboration. That and many of the tech giants have a paid version of the software that is easier for businesses to use or is more efficient in some way.


For example, Microsoft has Azure for managing SQL Server but has an open-source edition of SQL Server from 2019. This way tech giants can foster goodwill and help developers, who may end up working for them, grow and learn. While also making money off the same software at the same time.

Instance

The Definition for an instance with SQL databases can change depending on the software and service you use. In broad terms, the instance is the memory needed to pull your data. It also includes the software which changes depending on the service.


Aurora refers to their instances as virtual computing environments. An Aurora instance can have compute, memory, and storage capabilities. An EC2 instance is where Amazon’s EC2 optimizes it for memory and storage. Amazon EC2 is the Elastic Compute Cloud for AWS.


A DB instance in Aurora is the virtual environment where your database runs on the cloud. AWS protects the DB instance with a backup retention period of 1 to 35 days depending on what you choose. For any questions on Aurora DB instances, and other instances see their FAQ page.

Database or Db Clusters

The definition for an SQL database cluster can change a bit depending on the SQL database service. Generally clusters can be a collection of instances, but this definition will be pertinent to Amazon Aurora.


An Aurora cluster includes the collection of DB instances and the cluster volume. Cluster volume refers to Aurora’s storage volume, which gets stored in several Availability Zones (AZ). An Availability Zone is the AWS Region code, i.e. us-east-1a. You can choose the Availability Zone or it will be chosen for you. All DB instances get stored in 3 Availability Zones (unless it’s not available in your region). This way your data is backed up in multiple spaces.


The two kinds of instances Aurora stores in the AZ are your Primary DB Instance and Aurora Replica. Your Primary instance can be edited, while your Aurora Replica or read replicas, are read only copies.

DB Engine or Database Engine

A DB engine is the database management system DBMS, that you use to create and interact with your data. Your DB engine can be MySQL, PostgreSQL, MariaDB etc. The DB engine in Aurora can also be Aurora itself. It depends on what you choose for a DB engine while setting up.

I/O Input/Output, Throughput, Latency

I/O means the input/output. With Aurora this generally refers to the input/output of the storage. This is expressed in IOPS which is the amount of I/O per second.


Latency is the duration between your request and when it’s actually done. You can think of it as similar to loading time. Aurora recommends adding the Amazon Aurora Global Database, which has a latency of less than a second. It is an additional charge to use.


Throughput can be mean a coupled different things, the rate of production, the speed that your data takes to travel, capacity. For Aurora, when they talk about throughput they generally mean read/write throughput, which considers both capacity and latency and I/O. It is the amount of data transferred to the disk each second. In Aurora they measure throughput in megabytes per second MB/s.


For more information on storage and measurement see the RDS DB Instance storage article.

Snapshots

Snapshots in Aurora can be used to backup and transfer data. You can think of them as copies you can make of your DB instance or cluster.

Provisioning

The word provisioning can mean a number of different things. When referring to software its about managing/arranging data, storage, and infrastructure. When AWS Aurora uses it they mean infrastructure provisioning for your database, which can be arranging the structure, or managing resources.