Quotas and constraints for Amazon Aurora

Following, you can find a description of the resource quotas and naming constraints for Amazon Aurora.

Quotas in Amazon Aurora

Each AWS account has quotas, for each AWS Region, on the number of Amazon Aurora resources that can be created. After a quota for a resource has been reached, additional calls to create that resource fail with an exception.

The following table lists the resources and their quotas per AWS Region.

Resource	Default quota
Authorizations per DB security group	20
Concurrent DB snapshot export tasks	5
Cross-Region DB snapshot copy requests	5
Custom endpoints per DB cluster	5
Data API maximum result set size	1 MB
Data API requests per second	1000
DB clusters	40
DB cluster parameter groups	50
DB instances	40
DB subnet groups	50
Event subscriptions	20
AWS Identity and Access Management (IAM) roles per DB cluster	5
IAM roles per DB instance	5
Manual DB cluster snapshots	100
Parameter groups	50
Proxies	20
Reserved DB instances	40
Rules per virtual private cloud (VPC) security group	50 inbound, 50 outbound
Subnets per subnet group	20
Tags per resource	50
VPC security groups	5

Note

By default, you can have up to a total of 40 DB instances. RDS DB instances, Aurora DB instances, Amazon Neptune instances, and Amazon DocumentDB instances apply to this quota.

If your application requires more DB instances, you can request additional DB instances by opening the Service Quotas console. In the navigation pane, choose AWS services. Choose Amazon Relational Database Service (Amazon RDS), choose a quota, and follow the directions to request a quota increase. For more information, see Requesting a quota increase in the Service Quotas User Guide.

Backups managed by AWS Backup are considered manual DB cluster snapshots, but don't count toward the manual cluster snapshot quota. For information about AWS Backup, see the AWS Backup Developer Guide.

Naming constraints in Amazon Aurora

The following table describes naming constraints in Amazon Aurora.

Resource or item	Constraints
DB cluster identifier	Identifiers have these naming constraints: Must contain 1–63 alphanumeric characters or hyphens. First character must be a letter. Can't end with a hyphen or contain two consecutive hyphens. Must be unique for all DB instances per AWS account, per AWS Region.
Initial database name	Database name constraints differ between Aurora MySQL and PostgreSQL. For more information, see the available settings when creating each DB cluster.
Master user name	Master user name constraints differ for each database engine. For more information, see the available settings when creating each DB cluster.
Master password	The password for the database master user can include any printable ASCII character except /, ", @, or a space. Master password length constraints differ for each database engine. For more information, see the available settings when creating each DB cluster.
DB parameter group name	These names have these constraints: Must contain 1–255 alphanumeric characters. First character must be a letter. Hyphens are allowed, but the name cannot end with a hyphen or contain two consecutive hyphens.
DB subnet group name	These names have these constraints: Must contain 1–255 characters. Alphanumeric characters, spaces, hyphens, underscores, and periods are allowed.

Amazon Aurora size limits

Storage size limits

An Aurora cluster volume can grow to a maximum size of 128 tebibytes (TiB) for the following engine versions:

• Aurora MySQL engine versions 2.09 compatible with MySQL 5.70 and 1.23 compatible with MySQL 5.6.

• Aurora PostgreSQL engine versions 12.4 and higher, 11.7 and higher, 10.12 and higher, and 9.6.17 and higher.

For lower engine versions, the maximum size of an Aurora cluster volume is 64 TiB. For more information, see How Aurora storage automatically resizes.

SQL table size limits

For Aurora MySQL, the maximum table size is 64 tebibytes (TiB). For an Aurora PostgreSQL DB cluster, the maximum table size is 32 tebibytes (TiB). We recommend that you follow table design best practices, such as partitioning of large tables.