Amazon Aurora
Relational databases
Database as a service (DBaaS) providers
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What is Amazon Aurora
Amazon Aurora is a managed relational database service offered through Amazon Web Services that is compatible with MySQL and PostgreSQL. It is used by application teams and database administrators to run transactional workloads with managed provisioning, patching, backups, and scaling. Aurora separates compute from storage and supports features such as read replicas, Multi-AZ deployments, and global database options for cross-region replication. It is typically adopted by organizations standardizing on AWS-managed infrastructure for operational databases.
Managed operations on AWS
Aurora offloads common database administration tasks such as automated backups, point-in-time restore, patching, and monitoring through AWS tooling. It integrates with AWS identity, networking, encryption, and logging services commonly used in production environments. For teams already operating in AWS, this reduces the need to manage database servers directly compared with self-managed database software.
MySQL and PostgreSQL compatibility
Aurora offers engines that are wire-protocol compatible with MySQL and PostgreSQL, which can reduce application changes compared with adopting a different SQL dialect. This can simplify migrations from existing MySQL/PostgreSQL deployments while keeping standard client drivers and many ecosystem tools. It also supports common relational features needed for OLTP workloads, including transactions, indexes, and stored procedures (engine-dependent).
High availability and read scaling
Aurora supports Multi-AZ configurations and automated failover to improve availability for production workloads. It provides read replicas to scale read-heavy traffic and isolate reporting or read-only queries from primary write workloads. Options such as Aurora Global Database support cross-region replication patterns for disaster recovery and low-latency reads in multiple regions.
AWS lock-in and portability
Aurora is tightly integrated with AWS services and operational workflows, which can increase switching costs to other cloud providers or on-premises environments. While it is compatible with MySQL/PostgreSQL protocols, Aurora-specific behaviors and operational features may not translate directly to other managed or self-managed databases. Organizations with multi-cloud requirements may need additional abstraction or operational duplication.
Feature differences vs upstream
Aurora does not always match the exact feature set, extensions, or version cadence of community PostgreSQL or MySQL. Some engine features, extensions, or configuration controls may be limited or behave differently in a managed environment. This can affect workloads that rely on specific extensions, low-level tuning, or exact version parity.
Cost and scaling complexity
Pricing depends on instance class, storage, I/O, backups, and optional features, which can make total cost harder to predict than simpler deployments. Read scaling and high availability configurations add additional instances and cross-AZ or cross-region data transfer considerations. Teams often need ongoing monitoring and cost governance to avoid unexpected spend as workloads grow.
Plan & Pricing
Pricing model: Pay-as-you-go (mix of provisioned On‑Demand instance‑hours, Reserved Instances, and Serverless ACU‑based billing).
Free tier / trial (official):
- Data API free tier: 1,000,000 API requests per month, aggregated across Regions, for the first year. (time‑limited).
- AWS Free Tier provides 100 GB outbound data transfer per month (applies across AWS services). Note: there is no indication of a permanently free Aurora compute/storage tier on the Aurora pricing pages.
Example costs (official examples shown for US East (N. Virginia) on the Aurora pricing page):
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Aurora Serverless (ACU billing)
- Aurora Standard: $0.12 per ACU‑hour (example). Minimum capacity: 0.5 ACU.
- Aurora I/O‑Optimized: $0.156 per ACU‑hour (example).
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Provisioned (On‑Demand) instance examples
- db.r6i.large (Aurora Standard example): $0.29 per hour.
- db.r6i.large (Aurora I/O‑Optimized example): $0.377 per hour.
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Storage & I/O (Aurora Standard vs I/O‑Optimized)
- Storage (Aurora Standard): $0.10 per GB‑month (example).
- Storage (Aurora I/O‑Optimized): $0.225 per GB‑month (example, includes I/O).
- I/O (Aurora Standard): $0.20 per 1 million I/Os. Aurora I/O‑Optimized does not charge per‑I/O in examples.
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Data API
- $0.35 per 1 million API requests (example pricing). Data API free tier: 1M requests/mo for first year.
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CPU credits (T4g/T3 instances)
- CPU Credit charge: $0.09 per vCPU‑Hour (Aurora Standard) and $0.12 per vCPU‑Hour (Aurora I/O‑Optimized).
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Backup storage
- Backup storage is free up to 100% of the cluster volume size; additional backup/snapshot storage is metered per GB‑month (example used in docs: $0.021 per GiB‑month).
Discount / commitment options: Reserved Instances (1‑year / 3‑year) and Database Savings Plans are available for sustained/committed usage and can materially lower costs (examples and % savings shown on official pages).
Notes & caveats (official):
- Many prices vary by AWS Region and by DB engine (Aurora MySQL vs PostgreSQL) and by cluster configuration (Standard vs I/O‑Optimized). The Aurora pricing page provides per‑region tables and calculator links for region‑specific rates and detailed estimates.
- The figures above are the example/unit rates shown on the official Aurora pricing and Aurora Docs pages (US East examples). Always confirm region and engine on the official pricing page before budgeting.
Seller details
Amazon Web Services, Inc.
Seattle, Washington, USA
2006
Subsidiary
https://aws.amazon.com/
https://x.com/awscloud
https://www.linkedin.com/company/amazon-web-services/
