AXENTED — Blog Article

AWS vs GCP for LATAM Startups: What Actually Matters

Most cloud provider comparisons are written from a US-centric perspective. They compare pricing in US dollars, reference US-based compliance frameworks, and assume low latency to US East or US West coasts. For a startup based in Mexico City, Monterrey, or Bogotá, those comparisons miss the things that actually drive the decision.

Here's the comparison that matters for LATAM.

Latency from LATAM

AWS has a São Paulo region (sa-east-1) and a Mexico City Local Zone. GCP has São Paulo and Santiago regions. For applications with users primarily in Mexico or Central America, the differences in latency between the two providers' nearest regions are small — typically within 5–10ms for most user locations. For applications where latency is critical (real-time communication, gaming, financial trading), measure both providers from your actual user geography before deciding. For most applications, the latency difference is not the determining factor.

What matters more is which provider has the specific managed services you need available in the LATAM region. Not all AWS or GCP services are available in every region. Verify that the specific services in your architecture are available in your target region before committing to either provider.

Pricing in Local Currency

Both AWS and GCP bill in US dollars with invoices payable by credit card or wire transfer. For companies incorporated in Mexico, this creates FX exposure — as the peso weakens against the dollar, cloud costs increase in peso terms without any change in usage. Neither provider fully mitigates this, but both have local billing entities and tax receipt (facturación) capabilities for Mexican companies.

GCP has historically been more aggressive on committed use discount programs in LATAM. AWS has more flexible reserved instance options. For significant cloud spend, negotiating custom pricing with either provider is possible and worth doing at scale.

Data Residency and Compliance

Mexican data protection law (LFPDPPP) and emerging Mexican financial regulatory requirements are an active consideration for fintech, healthtech, and any company handling sensitive personal data. Both AWS and GCP have compliance documentation for Mexican regulatory requirements, but the depth of that documentation varies.

For regulated industries, work through the compliance implications with a legal advisor before selecting a provider. The technical team's preference for one provider or the other matters less than the compliance posture when auditors are involved.

Ecosystem and Talent

In the Mexican tech market, AWS certifications are more common than GCP certifications. The AWS ecosystem — third-party tools, integrations, documented architectures — is larger. This practical consideration matters for hiring and for finding solutions to operational problems.

GCP has strengths in data engineering and machine learning tooling (BigQuery, Vertex AI) that are relevant for analytics-heavy applications. For AI/ML workloads, GCP's managed ML infrastructure is often the more mature option.

Support Quality in Practice

Enterprise support contracts from both providers are expensive and, in our experience, variable in quality. For early-stage startups, community support (Stack Overflow, GitHub issues, provider documentation) is the primary resource for both AWS and GCP. Both have reasonable community resources; AWS's is larger simply due to market share.

The Practical Recommendation

For most LATAM startups: choose AWS if your team has more AWS experience, if ecosystem compatibility matters for your integrations, or if you need the widest range of managed services. Choose GCP if your workload is data-heavy, you're building ML infrastructure, or you've been offered a meaningful startup credit package (Google has been aggressive with GCP credits for startups).

The wrong reason to choose either: because it's what someone on the team used at their last job. Comfort with a provider is a real consideration, but it shouldn't override a meaningful technical or economic difference for your specific use case.