AWS is a comprehensive enterprise cloud platform with 200+ services and global reach, while DigitalOcean is a simplified, developer-focused cloud provider offering core infrastructure services at lower costs and with easier pricing models.
AWS vs DigitalOcean — Side-by-side comparison on A Versus B
Choose AWS if you need enterprise-grade scalability, advanced AI/ML services, global compliance certifications, and don't mind complexity or cost management challenges. Choose DigitalOcean if you're bootstrapping a startup, building straightforward web applications, value simplicity and predictable costs, and want to get running in minutes rather than hours.
Compare Amazon Web Services (AWS) vs DigitalOcean
Enterprise cloud computing platform offering 200+ services from compute to AI/ML to databases.
Developer-friendly cloud provider offering simplified Droplets, Kubernetes, and managed databases at transparent, flat-rate pricing.
Structured comparison data for AWS vs DigitalOcean with 182 attributes.
Monthly Cost (1 vCPU, 1GB RAM, Standard Instance)
Monthly Cost for 10TB Egress Data Transfer
Estimated Learning Time for New Developer
Cost for Standard Production App (2 dynos + add-ons)
Compute Instance Starting Price (hourly)
Cost for Production App (2 dynos/Droplets + DB)
Managed Kubernetes Pricing (Per Cluster)
AWS vs DigitalOcean — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for AWS vs DigitalOcean.
DigitalOcean is significantly cheaper for small projects. A basic DigitalOcean Droplet costs $5.99-$12/month with predictable pricing, while AWS's free tier covers limited usage and costs escalate quickly once you exceed thresholds. For a simple WordPress blog or API, DigitalOcean saves 70-80% annually.
Can I scale from DigitalOcean to AWS later?
Yes, but migration requires planning. Both use standard Linux/Docker, so applications are portable. However, AWS-specific services (Lambda, SageMaker, DynamoDB) have no direct DigitalOcean equivalents. Plan to refactor 20-40% of infrastructure if moving to leverage AWS's unique services.
Which is better for machine learning projects?
AWS is the clear winner with 40+ ML services including SageMaker, Rekognition, Forecast, and Textract. DigitalOcean doesn't offer managed ML services—you'd manually configure TensorFlow or PyTorch on a Droplet. AWS reduces ML deployment time by 60-70% through pre-built models and training pipelines.
How easy is it to estimate costs upfront?
DigitalOcean's pricing is transparent and predictable: a $12/month Droplet with 2GB RAM costs exactly that. AWS requires using their pricing calculator with 100+ variables (storage, data transfer, compute hours, service combinations), making accurate estimates difficult without expert analysis.
Which has better documentation for beginners?
DigitalOcean's documentation is beginner-friendly with step-by-step tutorials, often completable in 15-30 minutes. AWS documentation is comprehensive but dense, requiring 2-3 hours to deploy equivalent infrastructure. DigitalOcean's community tutorials are 10x more abundant for basic use cases.