Answer Details

If you’re a SaaS startup considering cloud infrastructure, here are the most highly recommended cloud providers — each with strengths worth evaluating, especially given your background in SaaS, ERP and data systems. ⸻ 1. Amazon Web Services (AWS) Why it stands out: • AWS remains the market-leader with very broad global coverage and service depth.  • For startups it offers credit programmes, accelerator support, and a huge ecosystem.  • It’s ideal if you anticipate scaling significantly, using diverse services (compute, storage, analytics, ML) or operating globally. Considerations: • Complexity and cost: With great breadth comes many configuration options and potential for unexpected expense if not managed well (especially relevant for data-intensive SaaS and ERP integrations). • Need to invest in governance, budgeting and cost-control from the start. Why it might fit you (given your profile): • Your background in ERP/data-management suggests you’ll benefit from a provider that supports complex architectures, integrations, hybrid data setups. • AWS offers mature tools for migration, data lakes, analytics and enterprise-style deployments. ⸻ 2. Microsoft Azure Why it stands out: • Azure is very strong in hybrid cloud, enterprise compatibility (especially if your target clients are larger corporates with Microsoft stacks).  • It has good startup programmes, integrations with Office/Microsoft ecosystem which may benefit SaaS firms focused on business users. Considerations: • While very capable, for pure “cloud native” startups some prefer AWS or Google for the breadth of newer services. • Pricing and support models vary, so early clarity is key. Why it might fit you: • If your SaaS targets enterprise customers who already run Microsoft/Windows/Active Directory/Office stacks, Azure gives you alignment. • Also useful if you foresee hybrid deployments (on-prem + cloud) for data migration / ERP wrap-around services. ⸻ 3. Google Cloud Platform (GCP) Why it stands out: • GCP is increasingly compelling, particularly if your SaaS has a strong data/analytics/ML dimension (which may align with your data-management interest).  • They have generous startup credit programmes (e.g., for early-stage startups) which can help manage initial cost.  • Developer-friendly and good for containerised & microservices architectures. Considerations: • Slightly smaller ecosystem compared to AWS in some geographies or service breadth.  • If you’re operating globally, check region/data-centre coverage relevant to your target markets. Why it might fit you nicely: • Given your focus on data migration/ERP/data management, GCP’s analytics and data-platform services can be a strong match. • If you want simplicity + developer-friendly tooling + an attractive startup credits offer, GCP is worth serious consideration. ⸻ 4. DigitalOcean Why it stands out: • DigitalOcean markets itself as startup-friendly: simpler pricing, more predictable bills, good for smaller teams/dev-led startups.  • If you want to launch quickly, with less tooling overhead, it’s a viable option. Considerations: • It may lack some of the enterprise-grade services (especially in analytics, advanced integrations or very large-scale global infrastructure) compared with AWS/Azure/GCP. • If you foresee rapid scaling or complex enterprise requirements, you’ll want to evaluate carefully. Why you might pick it (or keep it in mind): • If your SaaS startup is still in MVP/early stage, you might prioritise speed, cost-predictability and simplicity. • Then you could migrate later to a larger provider as you scale. ⸻ 5. Key factors to evaluate (for your SaaS/ERP/data-migration context) When choosing between these providers, here are aspects you should emphasise: • Startup credits / incentives: Early-stage cost control is vital. GCP and AWS both have strong startup programmes. • Service breadth vs simplicity: Do you need very advanced services (data lakes, ML, multi-region, hybrid) or a simpler stack? • Cost predictability & governance: For SaaS startups you want to avoid “bill shock”. Especially if you support large data migrations/integrations. • Data & integration capabilities: Since you work in ERP/data migration, ability to integrate with on-prem, legacy systems, hybrid, multi-cloud is key. • Global/regional presence: Since you’re based in Europe (Heidelberg) and might deal with European clients, check data-centre regions, compliance (GDPR), latency in EMEA. • Ecosystem & partner network: For ERP/data-migration you may need partner tools, marketplace integrations, managed services. • Vendor lock-in / portability: Consider how easy it might be to switch or use multi-cloud in future. • Support & roadmap: How strong is their startup/scale-up support? How future-proof are they for SaaS growth. ⸻ My recommendation for your specific situation Given your senior background in SaaS/ERP/data-management and your location in Heidelberg/European market, here’s how I’d prioritise: 1. Start with either GCP or AWS, depending on what your MVP/initial architecture looks like. If your product has strong data/analytics or integration angle, GCP is slightly more compelling; if you expect large scale, global reach and breadth of services, AWS might be slightly safer. 2. If early stage & cost sensitive, keep DigitalOcean in mind as a lean alternative, especially for MVP or initial launch. 3. Consider Azure if your target clients are enterprise European companies heavily invested in Microsoft stacks or hybrid/on-prem colour. 4. Design for scalability and migration: Even if you start with one provider, build with abstraction so you could switch or use multi-cloud later if needed (important given your data-migration domain). ⸻ If you like, I can compare pricing tiers, startup credit programmes, and specific tools relevant to SaaS/ERP/data-migration for the top providers (AWS, GCP, Azure, DigitalOcean) in a table — would you like that?