- Budget-constrained early-stage workloads
- For workloads that do not require Aurora’s high-availability or read-scaling features, Amazon RDS for PostgreSQL/MySQL can be materially cheaper and simpler.
- Need for true “scale to zero” compute for dev/test
- Aurora Serverless v2 has a configured minimum capacity and may not effectively reach zero compute cost in many practical configurations; organizations requiring zero-cost idle behavior should evaluate alternatives.
- Global active-active multi-writer requirements
- Aurora Global Database uses a primary-write model with read-only secondaries; workloads that require active-active multi-writer semantics should consider distributed SQL databases or alternative architectures.
- Requirement for identical upstream open-source behavior across environments
- Aurora is highly compatible with PostgreSQL/MySQL, but there are implementation differences; organizations seeking identical upstream behavior across on-prem and cloud should validate compatibility for their specific features.
- On-prem/hybrid management needs
- Aurora is a managed AWS service; organizations requiring the same managed control plane across on-prem and cloud may prefer self-managed or vendor solutions that support hybrid deployments.
- Documented limits and constraints
- Aurora Global Database and other features have documented limitations that vary by engine version and deployment mode; buyers should review the official limitations documentation for their intended configuration.
- Roadmap and lifecycle considerations
- Aurora Serverless v1 has reached end-of-support; organizations running v1 should plan migrations to supported configurations.
- Scale and architectural constraints
- Single-writer multi-region architectures can limit write scaling; common mitigations include vertical scaling, sharding, or adopting architectures designed for distributed writes.
- Serverless v2 minimum capacity behavior can affect idle-cost assumptions.
- Security and compliance considerations
- No specific compliance gaps were identified in the documentation reviewed, but compliance is shared responsibility; customers must configure network isolation, IAM policies, logging, key management, and monitoring to meet their control objectives.
- API and integration implications
- The Data API and other managed features may introduce separate metering and operational costs; design choices around proxies, secrets management, and audit logging affect cost and security posture.