NOTICE | On 3/31/25, Amazon Aurora Serverless v1 will no longer be supported. Learn how to upgrade to Aurora Serverless v2. >>
Amazon Aurora Serverless is an on-demand, autoscaling configuration for Amazon Aurora. It automatically starts up, shuts down, and scales capacity up or down based on your application's needs. You can run your database in the cloud without managing any database instances. You can also use Aurora Serverless v2 instances along with provisioned instances in your existing or new database clusters.
Manually managing database capacity can take up valuable time and can lead to inefficient use of database resources. With Aurora Serverless, you create a database, specify the desired database capacity range, and connect your applications. You pay on a per-second basis for the database capacity that you use when the database is active, and migrate between standard and serverless configurations with a few steps in the Amazon Relational Database Service (Amazon RDS) console.
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NEW: Amazon Aurora Serverless v2
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Amazon Aurora Serverless v1
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NEW: Amazon Aurora Serverless v2
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Amazon Aurora Serverless v2 scales instantly to hundreds of thousands of transactions in a fraction of a second. As it scales, it adjusts capacity in fine-grained increments to provide the right amount of database resources that the application needs. There is no database capacity for you to manage. You pay only for the capacity your application consumes, and you can save up to 90% of your database cost compared to the cost of provisioning capacity for peak load.
Aurora Serverless v2 supports all manner of database workloads. Examples include development and test environments, websites, and applications that have infrequent, intermittent, or unpredictable workloads to the most demanding, business critical applications that require high scale and high availability. It supports the full breadth of Aurora features, including global database, Multi-AZ deployments, and read replicas. Aurora Serverless v2 is available for the Amazon Aurora MySQL-Compatible Edition and PostgreSQL-Compatible Edition.
Benefits
Highly scalable
Scale instantly to hundreds of thousands of transactions in a fraction of a second.
Highly available
Power your business-critical workloads with the full breadth of Aurora features, including cloning, global database, Multi-AZ, and read replicas.
Cost effective
Scale out fine-grained increments to provide just the right number of database resources and pay only for capacity consumed.
Simple
Removes the complexity of provisioning and managing database capacity. The database will scale to match your application’s needs.
Transparent
Scale database capacity instantly, without disrupting incoming application requests.
Durable
Protects against data loss using the distributed, fault-tolerant, self-healing Aurora storage making your data durable across three Availability Zones (AZs) in a Region.
Use cases
Variable workloads
You're running an infrequently-used application, with peaks of 30 minutes to several hours a few times each day or several times per year, such as a human resources, budgeting, or operational reporting application. You no longer have to provision to peak capacity, which would require you to pay for resources you don't continuously use, or to average capacity, which would risk performance problems and a poor user experience.
Unpredictable workloads
You're running workloads with database usage throughout the day, and also peaks of activity that are hard to predict. For example, a traffic site that might see a surge of activity when it starts raining. Your database will automatically scale capacity to meet the needs of the application's peak load and scale back down when the surge of activity is over.
Enterprise database fleet management NEW
Enterprises with hundreds or thousands of applications, each backed by one or more databases, must manage resources for their entire database fleet. As application requirements fluctuate, continuously monitoring and adjusting capacity for each and every database to ensure high performance, high availability, and remaining under budget is a daunting task. With Aurora Serverless v2, database capacity is automatically adjusted based on application demand. You no longer need to manually manage thousands of databases in your database fleet. Features such as global database and Multi-AZ deployments ensure high availability and fast recovery.
Software as a service applications NEW
Software as a service (SaaS) vendors typically operate hundreds or thousands of Aurora databases, each supporting a different customer, in a single cluster to improve utilization and cost efficiency. But they still need to manage each database individually, including monitoring for and responding to colocate databases in the same cluster that may take up more shared resources than originally planned. With Aurora Serverless v2, SaaS vendors can provision Aurora database clusters for each individual customer without worrying about costs of provisioned capacity. It automatically shuts down databases when they are not in use to save costs and instantly adjusts databases capacity to meet changing application requirements.
Scaled-out databases split across multiple servers NEW
Customers with high write or read requirements often split databases across several instances to achieve higher throughput. However, customers often provision too many or too few instances, increasing cost or limiting scale. With Aurora Serverless v2, customers split databases across several Aurora instances and let the service adjust capacity instantly and automatically based on need. It seamlessly adjusts capacity for each node with no downtime or disruption, and uses only the amount of capacity needed to support applications.
How to get started
Aurora Serverless v2 is available for Aurora MySQL-Compatible and PostgreSQL-Compatible editions. It's easy to get started: choose Serverless v2 when creating your Aurora database cluster, specify the desired range of database capacity or use the defaults, and connect your applications.
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Amazon Aurora Serverless v1
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Amazon Aurora Serverless v1 is a simple, cost-effective option for infrequent, intermittent, or unpredictable workloads.
Benefits
Simple
Removes the complexity of provisioning and managing database capacity. The database will automatically start up, shut down, and scale to match your application’s needs.
Scalable
Seamlessly scale compute and memory capacity as needed, with no disruption to client connections.
Cost-effective
Pay only for the database resources you consume, on a per-second basis. You don't pay for the database instance unless it's actually running.
Highly available
Built on distributed, fault-tolerant, self-healing Aurora storage making your data durable across three Availability Zones in a Region to protect against data loss.
Use cases
Infrequently-used applications
You have an application that is only used for a few minutes several times per day or week, such as a low-volume blog site, and you want a cost-effective database that only requires you to pay when it's active. With Aurora Serverless v1, you only pay for the database resources you consume.
Development and test databases
Your software development and QA teams are using databases during work hours, but don’t need them on nights or weekends. With Aurora Serverless v1, your database automatically shuts down when not in use, and starts up much more quickly when work starts the next day.
How to get started
Aurora Serverless v1 is available for both Amazon Aurora with MySQL compatibility and Amazon Aurora with PostgreSQL compatibility. It's easy to get started: choose Serverless when creating your Aurora database cluster, optionally specify the desired range of database capacity, and connect your applications.
Customers
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British Airways
British Airways is a global airline, bringing people, places and diverse cultures closer together for more than 100 years.
Thanks to Amazon Aurora Serverless v2 and Data API, we can now parallelise our data analysis and processing within AWS Lambda. Instead of executing our data science workloads sequentially, we can run them concurrently. Lambda can seamlessly scale from zero to 200 or 300 functions running concurrently, and the Data API efficiently manages connection spikes. Consequently, data analysis for a single flight is now typically completed in less than 30 seconds, a significant improvement from the tens of minutes it used to take.
Nils Mohr, Senior Flight Data Software Engineer - British Airways -
CloudZero
CloudZero is the leader in cloud cost intelligence.
Amazon Aurora Serverless v2 and Data API enable us to avoid managing complex VPC’s and network access controls which significantly reduces our operational complexity and security burden. This means being able to focus on hiring more software engineers and less operations folks. We think of this as living the “Serverless lifestyle” where we rely on AWS for ensuring our uptime and availability which allows us to move faster with less headcount costs.
Erik Peterson, CTO/CISO & Founder - CloudZero -
Easygo
Easygo develops best-in-class gaming products using the latest technology for players worldwide. Easygo builds platforms like stake.com, which is the world’s leading Crypto Casino & Sports Betting platform, operating with 100 percent provably fair and transparent gambling with Bitcoin, Ethereum, Litecoin, and numerous other cryptocurrencies. Easygo needed a database solution which could handle tens of thousands of players concurrently during major sporting events such as the Soccer World Cup, NBA, or NFL seasons. With more players growing year over year, Easygo needed to scale and accommodate its ever-growing player base.
The highly variable nature of these sport-seasons workloads meant Easygo saw a rapid scale increase on top of its usual traffic patterns. We wanted the engineering team to spend less time managing database scaling requirements, and a database solution that could seamlessly scale to handle sporting events worldwide in different time zones. Easygo migrated roughly 50 databases over to Amazon Aurora Serverless v2, enabling the team to focus on building bigger and better games, while spending less time investigating bottlenecks.
Director of Engineering - Easygo -
Intuit
Intuit is a leading provider of financial management software for consumers, small businesses, and accounting professionals, with products including TurboTax, QuickBooks, Mint, Credit Karma, and Mailchimp.
Looking to reduce operational overhead and improve our database costs, we decided to utilize Amazon Aurora Serverless. Mixed-configuration clusters are perfect for our use case, which allows us to use a combination of provisioned Amazon Aurora writer and Amazon Aurora Serverless v2 readers within the same cluster. With Aurora Serverless v2, we get the benefits of automatic scaling without compromising on our requirement for high availability and disaster recovery. We use Aurora Serverless v2 in both our production and non-production environments, and it has helped us save approximately 55% on our database provisioning costs. With Aurora Serverless v2, our developers can focus more on building features and less on managing capacity.
Rajesh Saluja, Principal Data Engineer - Intuit -
S&P Dow Jones Indices
S&P Dow Jones Indices (S&P DJI), a business segment of S&P Global Inc., offers innovative indices and a range of leading-edge solutions to help investors identify, measure, and capitalize on global investment opportunities. S&P DJI has nearly 200 databases supporting its core applications, with sizes ranging from 500GB to 15TB.
We began our migration journey with Amazon Web Services (AWS) migrating from on-premises to MySQL on Amazon EC2 and then directly to Amazon Aurora MySQL-Compatible Edition, utilizing AWS Database Migration Service (AWS DMS). We recently adopted Aurora Serverless v2 for a new application that includes machine learning capabilities using AWS SageMaker for sector wide asset classification. Setting up AWS Glue jobs to ingest data from Twitter feeds led to a very dynamic workload for this application. Hence we adopted Aurora Serverless v2, which can scale the compute resources dynamically to support processing all the AWS Glue jobs and AWS Lambda functions, while being able to ingest massive volumes of data. We have also enabled write forwarding to keep our application active in more than one region, with Amazon Aurora Global Database.
Shivakumar Bangalore, Sr. Director of Database Engineering - S&P Global Inc.