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Cloud EngineeringMarch 19, 2026

AWS vs GCP for HIPAA-Compliant Healthcare Infrastructure

Both AWS and GCP can meet HIPAA requirements. The differences that matter are in managed service coverage, audit tooling, and how your team will operate the environment after handover.

KB

Karan Bhosale

Founder, Kinesiis

Healthcare IT teams evaluating cloud platforms for HIPAA-compliant infrastructure often frame the decision as AWS vs GCP (or Azure, but that is a separate comparison). Both platforms can meet HIPAA requirements. Both sign Business Associate Agreements. Both have the encryption, access control, and audit logging capabilities that compliance demands. The differences that actually affect your project are more practical: which managed services are covered under the BAA, how audit evidence is collected and presented, and which platform your internal team can operate after the engagement ends.

Key takeaways

  • -Both AWS and GCP sign BAAs and support HIPAA-compliant configurations. The compliance floor is equivalent. The differences are in operational details.
  • -AWS has broader HIPAA-eligible service coverage (200+ services vs approximately 90 on GCP). If your workload uses niche managed services, check BAA coverage before choosing.
  • -GCP's BigQuery is significantly easier to configure for HIPAA-compliant analytics workloads than AWS Redshift or Athena, especially for teams without dedicated database administrators.
  • -The best choice usually depends on your team's existing expertise. A compliant environment your team can operate is better than a theoretically superior one they cannot maintain.

BAA coverage: AWS covers more services

AWS includes over 200 services under its BAA. GCP covers approximately 90. For straightforward workloads (compute, storage, database, networking), both platforms have full coverage. The gap appears in niche managed services.

If your architecture uses a managed service for machine learning model training, a specific queue system, or a specialised analytics tool, verify that it falls under the BAA before designing around it. Using a non-BAA-covered service to process or store PHI means you cannot demonstrate compliance for that component.

In practice, most healthcare data infrastructure projects use a core set of 15-20 services (compute, storage, database, IAM, logging, networking, container orchestration). Both platforms cover these. The BAA coverage gap matters most for teams with complex, multi-service architectures.

Audit logging and evidence collection

HIPAA auditors want evidence that controls are in place, tested, and monitored. Both platforms provide this, but the tooling differs.

AWS CloudTrail logs API activity across all regions and services. AWS Config tracks resource configuration changes and can evaluate compliance rules continuously. Together, they produce the audit trail that compliance teams need. The tooling is mature but requires configuration: CloudTrail needs to be enabled in all regions, Config rules need to be defined, and log storage needs its own access controls.

GCP's Cloud Audit Logs provide equivalent functionality with a simpler default configuration. Admin activity logs are always on and cannot be disabled. Data access logs need to be enabled per service but the configuration is more centralised than AWS. For teams without dedicated cloud security engineers, GCP's audit logging is easier to set up correctly.

Data warehousing: BigQuery vs Redshift for healthcare analytics

Healthcare data infrastructure projects almost always include a data warehouse for operational and clinical analytics. This is where the platforms diverge most significantly in practice.

BigQuery is serverless, requires no cluster management, and scales automatically. For a hospital IT team that needs to run analytics queries on EHR data without managing database infrastructure, BigQuery is significantly easier to operate. Column-level security and row-level access policies can be configured to restrict PHI access by role.

Redshift requires cluster sizing, maintenance windows, and more active management. It offers better performance for complex joins on very large datasets and more control over query optimisation. For teams with dedicated database administrators, Redshift provides more tuning options.

For most healthcare data infrastructure projects where the IT team will operate the environment after handover, BigQuery's lower operational overhead is the deciding factor. The performance difference rarely matters at the data volumes typical of hospital network analytics.

The real deciding factor: your team's existing expertise

The compliance capabilities of AWS and GCP are close enough that the deciding factor is usually your team. If your IT team has three years of AWS experience and no GCP experience, building on GCP creates an operational risk that outweighs any platform advantage.

A compliant environment that your team can confidently operate, troubleshoot, and maintain is better than one built on a theoretically superior platform that your team struggles to manage after handover. This is especially true for healthcare organisations where the IT team is small and has other responsibilities beyond cloud infrastructure.

If your team has no cloud experience with either platform, the choice is more open. In that case, we typically recommend based on the specific workload: GCP for analytics-heavy projects (BigQuery advantage), AWS for projects with complex service requirements (broader BAA coverage).

In summary

AWS and GCP are both viable platforms for HIPAA-compliant healthcare infrastructure. The compliance floor is equivalent. The differences that matter are practical: BAA service coverage (AWS leads), audit logging ease (GCP is simpler to configure correctly), data warehouse operations (BigQuery is easier for small teams), and your team's existing expertise (which usually dominates the decision). Choose the platform your team can operate confidently. A well-run environment on either platform will pass an audit. A poorly operated environment on either platform will not.

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