Pay as you go with no up-front fees. There is no minimum fee. The prices below apply to both the MySQL-compatible and the PostgreSQL-compatible editions of Amazon Aurora, except where noted.
Select "MySQL-Compatible Edition" or "PostgreSQL-Compatible Edition" to view database instance pricing.
Database Storage and IOs
Storage consumed by your Amazon Aurora database is billed in per GB-month increments and IOs consumed are billed in per million request increments. You pay only for the storage and IOs your Amazon Aurora database consumes and do not need to provision in advance. IO charges may vary significantly depending on workload and database engine. To learn more visit the Aurora FAQ, “Q: What are IOs in Amazon Aurora and how are they calculated?”
For example, let's say you have a R5.2xlarge database, with 1000GB of storage with your application performing 100 writes/sec and 400 reads/sec constantly over a month. Using on-demand prices in N. Virginia, you would pay $1.16 * 730 hours or $846.8 for compute, 1,000GB * 0.10 Gb-mo or $100 for storage and (500 * 730 * 60 * 60)/(1 million) * $0.20 / million or $262.8 for IO charges. In comparison, for the same database if your application performs 50 writes/sec and 100 reads/sec your IO charges will be (150 * 730 * 60 * 60)/(1 million) * $0.20 / million or $78.84. This example didn't assume costs from any additional back up charges, read replicas, or additional features such as GlobalDB.
Amazon Aurora Global Database is an optional feature that provides low-latency global reads and disaster recovery from region-wide outages. You pay for replicated write I/Os between the primary region and each secondary region. The number of replicated write I/Os to each secondary region is the same as the number of in-region write I/Os performed by the primary region. Apart from replicated write I/Os, you pay standard Aurora rates for instances, storage, cross-region data transfer, backup storage, and Backtrack.
Backup storage for Amazon Aurora is the storage associated with your automated database backups and any customer-initiated DB cluster snapshots. Increasing your backup retention period or taking DB cluster snapshots increases the backup storage consumed.
- Backup storage is allocated by region. Total backup storage space is equivalent to the sum of the storage for all backups in that region.
- Moving a DB cluster snapshot to another region increases allocated backup storage in the destination region.
- There is no additional charge for backup storage of up to 100% of your total Aurora database storage for each Aurora DB cluster. There is also no additional charge for backup storage if your backup retention period is 1 day and you don’t have any snapshots beyond the retention period.
- Backup storage, as well as snapshots you store after your DB cluster is deleted will be charged at the following rates:
Backtrack lets you quickly move an Aurora database to a prior point in time without needing to restore data from a backup. This lets you quickly recover from user errors, such as dropping the wrong table or deleting the wrong row. This feature is currently available for the MySQL-compatible edition of Aurora.
You need to specify how far in the past you want to be able to go (e.g. “up to 24 hours”). Aurora will retain logs, called Change Records, for the specified Backtrack duration. You pay a simple hourly rate for storing Change Records.
For example, suppose your Aurora database is generating 10,000 Change Records per hour – which you can see by reviewing your CloudWatch metrics – and you want to be able to use Backtrack up to 10 hours in the past. To support this, Aurora would need to store 10,000 Change Records/hour x 10 hours = 100,000 Change Records. Say the cost in the US East (N. Virginia) Region is $0.012/hour per 1 million Change Records. Then turning on Backtrack would increase your costs by $0.012 x (100,000 / 1,000,000) = $0.0012/hour.
When using Backtrack, you can review CloudWatch metrics in the AWS Console to see how many Change Records your database is generating per hour.
Amazon Relational Database Service (RDS) Snapshot Export provides an automated method to export data within an RDS or Aurora snapshot to Amazon S3 in Parquet format. The Parquet format is up to 2x faster to unload and consumes up to 6x less storage in Amazon S3, compared to text formats. You can analyze the exported data using AWS services such as Amazon Athena, Amazon EMR, and Amazon SageMaker.
The pricing below is based on data transferred “in” and “out” of Amazon Aurora.
- Data transferred between Amazon Aurora and Amazon EC2 instances in the same Availability Zone is free.
- Data transferred between Availability Zones for DB cluster replication is free.
- For data transferred between an Amazon EC2 instance and Amazon Aurora DB instance in different Availability Zones of the same Region, Amazon EC2 Regional Data Transfer charges apply.
Except as otherwise noted, our prices are exclusive of applicable taxes and duties, including VAT and applicable sales tax. For customers with a billing address in Japan, use of AWS is subject to Japanese Consumption Tax. Learn more.