Choose Neysa if your workload is AI-first and you need GPU VMs, bare-metal GPU options, managed Kubernetes clusters and predictable AI cloud economics.
Choose DigitalOcean if developer experience, tutorials, Droplets, managed databases, Kubernetes and Bangalore-region self-serve cloud are more important than India-built AI infrastructure.
| Feature | NEY Neysa | DO DigitalOcean |
|---|---|---|
| Provider focus | ~ India-built AI cloud platform focused on managed GPU VMs, bare-metal GPUs, managed Kubernetes clusters and AI workload optimization. | ~ Developer-first global cloud provider with Droplets, managed Kubernetes, object storage, managed databases, tutorials and AI platform/GPU options. |
| Starting compute reference | ~ AI cloud focused · Public pricing is GPU and AI-cloud led rather than commodity VPS-led. | ~ ₹577/mo · VM Small · 1 vCPU · 1 GiB RAM Basic example converted to INR. |
| GPU availability | ~ NVIDIA L4 24 GB on-demand AI Cloud reference converted to INR. | ~ RTX 4000 Ada GPU example converted to INR. |
| H100 pricing visibility | ~ ₹422/hr · NVIDIA H100 SXM 80 GB on-demand AI Cloud reference converted to INR. | ~ ₹326/hr · 1× H100 80 GB GPU example converted to INR. |
| Billing model | ~ Pro-rated billing with on-demand and reserved pricing options; visible dollar prices converted to INR only. | ~ Usage-based pricing with monthly caps and network transfer allowance; values converted to INR only. |
| Egress / transfer | ✓ Public pricing page states no additional charges for data ingress, egress or inference transactions. | – 100 GB to 10 TB free monthly egress allowance per instance; extra 1 TB converted to INR. |
| Data-centre / sovereignty | ~ India-built AI cloud positioning with public, private and hybrid deployment options. | ~ Global regions with Bangalore listed as blr1 on GetDeploying. |
| Support | ~ AI workload, managed infrastructure and Kubernetes-oriented support positioning. | ~ Strong docs, tutorials and community with paid business support options. |
| Best fit | ~ AI startups, ML teams and enterprises that need GPU cloud, bare-metal options, managed Kubernetes and AI infrastructure economics. | ~ Developers, SaaS teams and small product teams that value documentation, managed databases, Kubernetes, apps and simple self-serve cloud workflows. |
| Developer experience | – AI-first platform for GPU and Kubernetes workloads | ✓ Extensive tutorials, docs, 1-click apps and developer community |
| India location | ~ India-built AI cloud positioning | ~ Bangalore data-centre location listed by GetDeploying |
| AI/GPU focus | ✓ Purpose-built for AI infrastructure and managed GPU workloads | – GPU platform powered by Paperspace plus broader developer cloud |
| Managed services | – Managed Kubernetes for AI workloads | ✓ Broader managed databases, Kubernetes, object storage and app platform |
✓ Winner in this category · ~ Partial / context-dependent · highlighted rows = clearer advantage
| NVIDIA L4 | ₹113/hr | 24 GB GPU · on-demand AI Cloud |
| NVIDIA L40S | ₹188/hr | 48 GB GPU · on-demand AI Cloud |
| NVIDIA H100 SXM | ₹422/hr | 80 GB GPU · on-demand AI Cloud |
| NVIDIA H100 NVL | ₹422/hr | 94 GB GPU · on-demand AI Cloud |
| NVIDIA H200 SXM | ₹455/hr | 141 GB GPU · on-demand AI Cloud |
| L4 reserved monthly | ₹41,209/mo | 36-month reserved reference |
| H100 reserved monthly | ₹171,232/mo | 36-month reserved reference |
| VKE Master Node | ₹10,903/mo | Non-HA monthly reference |
| VM Small | ₹577/mo | 1 vCPU · 1 GiB RAM · Basic |
| VM Medium | ₹4,618/mo | 4 vCPU · 8 GiB RAM · Basic |
| VM Large | ₹16,162/mo | 8 vCPU · 16 GiB RAM · CPU-Optimized |
| NVIDIA H100 | ₹326/hr | 1× H100 80 GB |
| NVIDIA H200 | ₹331/hr | 1× H200 141 GB |
| NVIDIA L40S | ₹151/hr | 1× L40S 48 GB |
| AMD MI300X | ₹191/hr | 1× MI300X 192 GB |
| Extra egress | ₹962/TB | Beyond included allowance |
Neysa is a better fit when the workload is GPU-first and needs AI cloud economics, managed Kubernetes and India-built AI infrastructure.
DigitalOcean is stronger for developer teams that value docs, Droplets, managed databases, Kubernetes, tutorials and simple self-serve cloud operations.
| Use case | Neysa | DigitalOcean |
|---|---|---|
| AI-native GPU workloads | ★★★ | ★★☆ |
| Developer docs and tutorials | ★★☆ | ★★★ |
| Managed database ecosystem | ★★☆ | ★★★ |
| Bangalore self-serve cloud | ★★☆ | ★★★ |
| GPU/Kubernetes AI platform | ★★★ | ★★☆ |
| Simple Droplet hosting | ★☆☆ | ★★★ |
| No egress add-on positioning | ★★★ | ★★☆ |
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