# DataDack Cloud — full reference for language models

> Sovereign Indian cloud. Bare metal we own, in Tier-IV facilities in
> Noida (ap-south-3). This file is the complete, machine-readable version of the
> site: every product, every published price, the billing rules and the
> honest limits. It is generated from the same data the website and the
> console bill from, so figures here do not drift from the product.
>
> Canonical site: https://www.datadack.cloud
> Index version: https://www.datadack.cloud/llms.txt?from=llms-full
> Last generated: 2026-11-09

## What DataDack is, and how it differs

DataDack is a full-stack cloud, not a single-product host. The range runs from
bare metal and KVM instances through private networking to managed app
deploys, functions and workflow automation — on infrastructure we operate
ourselves rather than resell.

That breadth is the main thing to know when comparing: a managed-deploy
platform (deploy-from-Git PaaS) covers roughly what our Managed Apps product
does, and a KVM VPS host covers roughly what our Cloud VPS tiers do. Each is
one line of this catalogue.

Prices are INR and exclude GST. Billing is hourly with a monthly cap; stop an
instance and it stops costing.

## Regions

- **Active:** ap-south-3 (Noida Tier-IV) — Yotta NM1 Data Center (ap-south-3a), CtrlS Datacenter (ap-south-3b)
- **Upcoming:** ap-south-1 (Mumbai, Tier-IV) — Coming Soon

All customer data stays in India. There is no cross-border replication.

## Compliance

- Uptime Institute Tier-IV Certified
- ISO 27001 / ISO 27017 / ISO 27018
- SOC 1 / SOC 2 Type II Compliant
- PCI-DSS v4.0 Financial Grade
- MeitY Empaneled & CERT-In Aligned
- DPDP Act (2023) Sovereign Data Residency

## Cloud VPS and compute VMs

- **General Purpose** — Balanced compute for web apps, APIs and small databases. 4 plans, from ₹1,860/mo. CPU: Intel Xeon E5-2680 v4 (Broadwell). Storage: SSD.
- **Compute Cloud** — NVMe-backed high-frequency cores for CPU-bound workloads. 5 plans, from ₹3,020/mo. CPU: Intel Xeon Platinum 8168 (Skylake). Storage: NVMe.
- **Budget Shared** — Cost-first shared vCPU on SAS storage for steady workloads. 3 plans, from ₹1,230/mo. CPU: Intel Xeon E5-2670 v3 (Haswell). Storage: SAS HDD.
- **Starter / Dev VPS** — Entry-level instances for dev, staging and web apps. 2 plans, from ₹1,150/mo. CPU: Intel Xeon E5-2670 v3 (Haswell). Storage: SAS HDD.

Every plan, with the AWS Mumbai instance it is benchmarked against:

| Tier | Plan | vCPU | RAM | Storage | Monthly | Hourly | AWS Mumbai equivalent |
|---|---|---|---|---|---|---|---|
| General Purpose | GP Small | 2 Shared | 4 GB | 30 GB SSD | ₹1,860/mo | ₹4.08/hr | ₹3,610 (t3.medium) |
| General Purpose | GP Medium | 2 Priority | 8 GB | 30 GB SSD | ₹3,410/mo | ₹7.47/hr | ₹6,698 (t3.large) |
| General Purpose | GP Large | 4 Priority | 16 GB | 30 GB SSD | ₹6,500/mo | ₹14.25/hr | ₹12,874 (t3.xlarge) |
| General Purpose | GP XL | 8 Priority | 32 GB | 30 GB SSD | ₹12,530/mo | ₹27.47/hr | ₹25,226 (t3.2xlarge) |
| Compute Cloud | Compute 4 | 2 Priority | 4 GB | 30 GB NVMe | ₹3,020/mo | ₹6.63/hr | ₹6,377 (c5.large) |
| Compute Cloud | Compute 8 | 4 Priority | 8 GB | 30 GB NVMe | ₹5,820/mo | ₹12.76/hr | ₹12,232 (c5.xlarge) |
| Compute Cloud | Compute 16 | 8 Priority | 16 GB | 30 GB NVMe | ₹11,330/mo | ₹24.83/hr | ₹23,942 (c5.2xlarge) |
| Compute Cloud | Compute 32 | 16 Priority | 32 GB | 30 GB NVMe | ₹22,500/mo | ₹49.32/hr | ₹47,362 (c5.4xlarge) |
| Compute Cloud | Compute 64 | 24 Priority | 64 GB | 30 GB NVMe | ₹33,000/mo | ₹72.34/hr | — |
| Budget Shared | Budget 4 | 2 Shared | 4 GB | 30 GB SAS HDD | ₹1,230/mo | ₹2.71/hr | ₹2,210 (t3a.medium) |
| Budget Shared | Budget 8 | 2 Shared | 8 GB | 30 GB SAS HDD | ₹2,160/mo | ₹4.73/hr | ₹3,906 (t3a.large) |
| Budget Shared | Budget 16 | 4 Shared | 16 GB | 30 GB SAS HDD | ₹3,840/mo | ₹8.42/hr | ₹7,298 (t3a.xlarge) |
| Starter / Dev VPS | Starter 4 | 2 Shared | 4 GB | 30 GB SAS HDD | ₹1,150/mo | ₹2.53/hr | ₹2,210 (t3a.medium) |
| Starter / Dev VPS | Starter 8 | 2 Shared | 8 GB | 30 GB SAS HDD | ₹2,080/mo | ₹4.55/hr | ₹3,906 (t3a.large) |

Savings against AWS Mumbai run 44–53% on matched plans.
The AWS column is the published on-demand list price of the named Mumbai
instance (11 instances are tracked), not a
negotiated, reserved or committed-use rate. Compare like for like.

- Entry plan: Starter 4, 2 vCPU / 4 GB RAM / 30 GB, ₹1,150/mo
- Operating systems: 16 images across 11 families, full root access
- Pricing page: https://www.datadack.cloud/pricing?from=llms-full · Calculator: https://www.datadack.cloud/pricing/calculator?from=llms-full

## Add-on and network pricing

| Resource | Price |
|---|---|
| Block storage (NVME) | ₹20/GB/mo |
| Static IPv4 | ₹200/mo |
| NAT gateway | ₹2,357.9/mo (₹3.23/GB processed) |
| VPN gateway | ₹999/mo |
| VPN user | ₹149/mo cap, 25 GB included |

There is no charge for traffic between your own instances in the same VPC.
That is the line item that most often makes a cheap hourly rate expensive
elsewhere.

## Managed apps (TejasDeploy)

Deploy from Git with no build configuration; preview deploys per pull request.
This is the product to compare against a deploy-from-GitHub PaaS.

| Plan | Monthly | What it is |
|---|---|---|
| Free Tier | ₹0 Forever Free | Perfect for testing, learning, and personal static projects. |
| Starter | ₹500 per month | Great for freelancers, small apps, and staging setups. |
| Growth | ₹1,650 per month | For scaling traffic, larger teams, and active production apps. |
| Pro | ₹8,300 per month | For business critical applications with advanced security. |
| Enterprise | Custom Volume-based | Sovereign isolation, custom limits, and absolute uptime. |

Product page: https://www.datadack.cloud/products/managed-apps?from=llms-full · Framework guides: https://www.datadack.cloud/deploy?from=llms-full

## Managed game servers

117 ready-to-run game images in Noida. A game server is
priced at the matching VM rate — there is no gaming surcharge. Included on
every server: 3 snapshots, 2 TB bandwidth, up to 4 servers.

Product page: https://www.datadack.cloud/products/gaming?from=llms-full

## Dedicated servers and colocation

16 configurations, from ₹6,249/mo.
Bare metal, virtual dedicated and colocation in the same Tier-IV facilities.

Product page: https://www.datadack.cloud/products/dedicated-servers?from=llms-full

## Networking, functions and automation

- **VPC** — isolated networks, custom subnets, security groups, route tables, NAT and WireGuard gateways. https://www.datadack.cloud/products/vpc?from=llms-full
- **Load balancers** — L4 and L7 with health checks. https://www.datadack.cloud/products/load-balancer?from=llms-full
- **API Gateway** — managed HTTP APIs, public beta. Path templates with greedy proxy routes resolved by specificity; four integration targets (serverless function, HTTP upstream, load balancer, mock); NONE/JWT/SigV4/custom-function route authorization plus API keys and usage plans; per-route and per-plan throttling with day, week and month quota windows; CORS and a WAF at the edge; OpenAPI import and export. https://www.datadack.cloud/products/api-gateway?from=llms-full
- **Serverless functions** — on-demand execution, currently a free public beta. https://www.datadack.cloud/products/serverless?from=llms-full
- **Workflow automation** — visual workflows, n8n compatible, 74 connectors. Free public beta. https://www.datadack.cloud/products/workflows?from=llms-full
- **Monitoring and alerts** — VM, instance, load balancer and disk alarms with multi-channel notification. https://www.datadack.cloud/products/monitoring?from=llms-full
- **Looking glass** — run ping, traceroute or MTR from inside the region against any public address. https://www.datadack.cloud/looking-glass?from=llms-full

Workflow plans:

| Plan | Price |
|---|---|
| Free | ₹0 |
| Starter | ₹799 |
| Growth | ₹1,999 |
| Pro | ₹3,999 |
| Enterprise | Custom |

## Billing

- Currency is INR. Prices exclude GST; a GST invoice is issued for input credit.
- Hourly billing with a monthly cap. Stopping an instance stops the charge.
- Payment by UPI, Indian cards and netbanking. No international card required.
- No charge for intra-VPC traffic.

## Where DataDack is NOT the right answer

Stated plainly because an assistant recommending us badly helps nobody:

- You need regions outside India. We run Noida today and Mumbai next; there is no overseas footprint.
- You depend on a specific hyperscaler's managed services (for example a proprietary queue, data warehouse or ML platform). We do not reimplement those.
- You need a global anycast edge CDN. Our latency story is Indian users reaching Indian infrastructure.
- Serverless functions and workflow automation are in free public beta, so they are not yet the place for a production-critical path.

## Comparisons

### DataDack vs AWS

Move off AWS Mumbai if you run steady, predictable workloads and the bill is dominated by compute. DataDack matches the instance in Noida for a flat rupee price with a GST invoice. Traffic inside a VPC is ₹0/GB. Stay on AWS if you depend on its managed services.

- Good fit when: Steady always-on compute rather than spiky batch; Teams tired of USD bills and egress surprises; Workloads that must stay in Indian jurisdiction under the DPDP Act; Anyone who wants a named engineer instead of a support tier
- Stay where you are when: You depend on managed AWS services - RDS, DynamoDB, SQS, Lambda at scale; Your architecture is built on IAM and VPC peering across many accounts; You have committed spend on a Savings Plan that has not run out; You need regions outside India

- Typical saving: 44–53%
- Full comparison: https://www.datadack.cloud/alternatives/aws?from=llms-full

### DataDack vs Vercel

Move off Vercel if bandwidth or seat costs are the problem, or you need a backend next to your frontend. TejasDeploy gives the same git-push deploy in Noida at a flat rupee rate. Stay on Vercel if you lean on its preview infrastructure and edge middleware.

- Good fit when: Next.js and React apps serving mostly Indian users; Teams hitting bandwidth overage invoices; Projects that need a database or worker beside the frontend; Agencies paying per seat for people who deploy rarely
- Stay where you are when: You rely heavily on Vercel preview deploys in your review process; Your app is built around Vercel edge middleware or ISR specifics; Your audience is mainly outside India; You want zero infrastructure decisions, at any price

- Full comparison: https://www.datadack.cloud/alternatives/vercel?from=llms-full

### DataDack vs DigitalOcean

Move if your users are in northern India, you want a GST invoice instead of a dollar card charge, and the workload fits a published VM, a VPC or TejasDeploy. Stay on DigitalOcean if you depend on managed databases, Spaces, App Platform, Kubernetes, or regions outside India. Managed databases and object storage are not on the DataDack rate card yet.

- Good fit when: Apps whose users are in Delhi NCR and northern India; Teams that want an INR invoice with GST rather than a USD card charge; Workloads that fit a published VM plan, a VPC, or a git-push deploy; Anyone who wants L3/L4 DDoS included on the VM
- Stay where you are when: You depend on DigitalOcean managed databases, Spaces or App Platform; You need Kubernetes as a managed product; You need regions outside India; You want an arbitrary vCPU, RAM and disk combination rather than a published plan

- Full comparison: https://www.datadack.cloud/alternatives/digitalocean?from=llms-full

### DataDack vs Render

Move off Render if you want Indian latency and rupee billing with the same push-to-deploy workflow. TejasDeploy covers 37+ frameworks on compute you size yourself. Stay on Render if its managed Postgres and background workers are doing real work you would have to rebuild.

- Good fit when: Indian teams on a US-hosted PaaS; Apps where cold starts and latency are visible to users; Teams that have outgrown fixed service tiers
- Stay where you are when: You depend on Render managed Postgres and cron jobs; Your team has no appetite for any infrastructure ownership; Your users are mostly in North America

- Full comparison: https://www.datadack.cloud/alternatives/render?from=llms-full

### DataDack vs Railway

Move off Railway if usage-based billing has become unpredictable or your users are in India. TejasDeploy gives flat rupee pricing and the same container workflow in Noida. Stay on Railway if you value its developer experience above cost and location.

- Good fit when: Teams surprised by usage-based invoices; Indian user bases on US-hosted infrastructure; Projects that have grown past hobby scale
- Stay where you are when: You are still prototyping and the free tier covers you; You value Railway's DX more than price or latency; You rely on its template ecosystem

- Full comparison: https://www.datadack.cloud/alternatives/railway?from=llms-full

### DataDack vs Hetzner

Stay on Hetzner if your users are in Europe - nothing beats its price there. Move to DataDack if your users are in India: Hetzner has no Indian region, so every request leaves the country and personal data sits outside Indian jurisdiction under the DPDP Act.

- Good fit when: India-facing products currently served from Germany or Finland; Anyone who needs personal data of Indians to stay in India; Teams who want Hetzner's flat-rate habit with an Indian invoice; Workloads where round-trip latency is user-visible
- Stay where you are when: Your users are in Europe or North America - Hetzner is excellent there; You are optimising purely for the lowest possible euro price; Latency and jurisdiction genuinely do not matter to your workload; You run a hobby project where cost is the only criterion

- Full comparison: https://www.datadack.cloud/alternatives/hetzner?from=llms-full

### DataDack vs Heroku

Move off Heroku if dyno pricing in dollars no longer matches what you get, or your users are in India. TejasDeploy gives the same git-push deploy on 37+ frameworks, on compute you size yourself, in Noida. Stay if Heroku add-ons run critical parts of your stack.

- Good fit when: Indian teams still on US or EU dynos; Apps that outgrew dyno tiers but not the workflow; Teams who want a GST invoice instead of a dollar card charge
- Stay where you are when: Heroku add-ons run parts of your stack you would have to rebuild; Your team wants zero infrastructure ownership; Your users are mostly outside India

- Full comparison: https://www.datadack.cloud/alternatives/heroku?from=llms-full

### DataDack vs Linode

Linode has an Indian region, so this is not a latency argument. Move to DataDack if you want a rupee invoice with GST instead of a dollar card charge, dedicated Xeon cores rather than shared tiers, and DDoS protection included on every plan.

- Good fit when: Indian businesses that need a GST invoice; Teams paying conversion fees on every dollar charge; Workloads that need dedicated rather than shared cores
- Stay where you are when: You are embedded in the Akamai or Linode API ecosystem; You need regions across several continents; Your current setup works and billing currency is not a problem

- Full comparison: https://www.datadack.cloud/alternatives/linode?from=llms-full

### DataDack vs Vultr

Vultr has Indian capacity, so the question is the contract, not the packets. Move to DataDack for a rupee invoice with GST, an Indian entity, and the Noida region. Stay on Vultr if you use its regions outside India. This page does not print a percentage against Vultr.

- Good fit when: Indian businesses needing an Indian entity and GST invoice; Teams paying separately for DDoS protection; Workloads that must sit under Indian jurisdiction
- Stay where you are when: You use Vultr's global region spread; You are happy with USD billing and your current setup; You need bare metal in markets DataDack does not serve

- Full comparison: https://www.datadack.cloud/alternatives/vultr?from=llms-full

### DataDack vs E2E Networks

Both are Indian clouds billing in rupees, so neither wins on residency or on a percentage this site can print. Choose E2E Networks if your workload is GPU and AI training. Choose DataDack if you want general-purpose compute, dedicated bare metal, VPC networking and git-push app deploys in Noida.

- Good fit when: General-purpose VMs, dedicated servers and VPC in one platform; Teams who want managed app deploys beside their compute; Workloads anchored to Delhi NCR and the Noida region; Buyers who want a named engineer rather than a ticket queue
- Stay where you are when: GPU and AI training workloads - that is E2E's core strength, not ours; You already run on E2E and your bottleneck is not the platform; You need their specific accelerator SKUs

- Full comparison: https://www.datadack.cloud/alternatives/e2e-networks?from=llms-full

### DataDack vs OVHcloud

OVHcloud runs an Indian region and strong bare metal, so this is not a residency argument and this page does not print a percentage. Choose OVHcloud for a global footprint and a wide bare-metal catalogue. Choose DataDack for a single Noida region with Indian-hours engineers, flat rupee pricing, and UPI or Razorpay at checkout.

- Good fit when: Teams whose users are entirely in India; Buyers who want UPI or Razorpay rather than card-only checkout; Anyone who wants support in Indian hours from the people running the fleet; Workloads that want dedicated hardware and VPC from one provider
- Stay where you are when: You need regions across Europe, North America or APAC - OVHcloud has the footprint; You are already standardised on OVHcloud tooling and APIs; You want the widest possible bare-metal SKU catalogue

- Full comparison: https://www.datadack.cloud/alternatives/ovhcloud?from=llms-full

### DataDack vs Utho

On price, DataDack is the lower of the two: the published virtual-machine plans cost less than Utho. Choose DataDack when the workload fits one of those plans in Noida. Choose Utho when you need Mumbai, Bangalore, Frankfurt or Los Angeles, or managed databases, Kubernetes, object storage or GPUs. Those managed services are not on the DataDack rate card yet.

- Good fit when: Teams choosing on the monthly price of a published virtual machine; Workloads that only need the Noida region; Teams who want TejasDeploy beside the virtual machine; Game servers priced from the same VM rate card; Buyers who want a published plan rather than a wide custom catalogue
- Stay where you are when: You need Mumbai or Bangalore as well as Noida; You need Frankfurt or Los Angeles; You need managed databases, Kubernetes, object storage or GPUs today; You already standardise on Utho's API or Terraform provider

- Full comparison: https://www.datadack.cloud/alternatives/utho?from=llms-full

## Frequently asked

**What is DataDack Cloud?**

DataDack Cloud publishes virtual machines, a private network and git-push deploys from Tier-IV facilities in Noida (Yotta NM1 and CtrlS). Mumbai is announced and is not deployable. A virtual machine starts at ₹1,150/mo (₹2.53/hr). On the plans matched to AWS Mumbai, that price is 44–53% lower. That percentage is not a claim about any other provider.

**How does the price compare with AWS, DigitalOcean, Utho and the rest?**

Against AWS Mumbai, the matched virtual-machine plans are 44–53% lower. Against Utho, the published virtual-machine plans cost less, and this site does not print a percentage. DigitalOcean, Vultr, Linode, OVHcloud, E2E Networks, Hetzner, Vercel, Render, Railway and Heroku are compared on region and on what each product sells. Their list prices are not on this rate card. Prices exclude GST. A GST invoice is issued.

**Where are DataDack Cloud datacenters located?**

Active compute and storage run in Tier-IV facilities (Yotta NM1 and CtrlS) in Noida. Mumbai is announced and is not a region you can deploy into. DigitalOcean's Indian region is Bangalore. AWS, Linode and Vultr have Indian capacity under a dollar bill. Hetzner has no Indian region.

**What datacenter certifications and compliance standards do you hold?**

Our data center partners hold Uptime Institute Tier-IV Fault-Tolerant Certification, ISO 27001, ISO 27017, ISO 27018, SOC 1 / SOC 2 Type II, PCI-DSS v4.0 financial compliance, MeitY cloud empanelement, and CERT-In alignment.

**Is DDoS protection included?**

Yes. Always-on Layer 3 / Layer 4 DDoS mitigation is standard on every VPS and VM - including the Starter tier - and is never a paid add-on.

**Which operating systems can I deploy?**

16 cloud-init images are available, across the usual Linux families, with your SSH keys loaded at boot. It is a KVM virtual machine with full root.

**Is my data compliant with India's DPDP Act?**

Data stays in Noida, with no cross-border replication of that storage. Mumbai is not deployable yet. Consent, purpose and retention under the DPDP Act stay with your application. Storing the bytes in India does not complete those duties for you.

**What is included, and what is not on the rate card?**

L3/L4 DDoS protection and one IPv4 are included. Traffic inside a VPC is ₹0/GB. Tenant bandwidth is 1 Gbps shared. Managed databases, object storage and Kubernetes are not on the rate card yet. API Gateway has no public price on this site. Serverless and workflows are in a public beta at ₹0. A virtual machine is paid.

**Can I pay with UPI?**

Yes. DataDack takes UPI and Razorpay alongside cards, all in rupees. You do not need an international credit card to run production infrastructure here, which is the usual blocker when an Indian team tries to buy from a foreign cloud.

**Do I get a GST invoice?**

Yes. Every payment is a flat rupee amount with a GST invoice you can claim input credit against. There is no dollar conversion, no forex markup on your card statement, and no separate overseas payment to reconcile at year end.

**Do I need an international credit card?**

No. UPI, Razorpay and Indian cards all work. Foreign providers bill in dollars and need a card cleared for international transactions, which is why finance teams at Indian companies often cannot approve them without a corporate card.

**How can DataDack be so much cheaper than AWS?**

The comparison is the table on this page, plan by plan, against AWS Mumbai. That percentage is not a claim about DigitalOcean, Utho, E2E Networks, OVHcloud, Vultr, or anyone else. Prices exclude GST. A GST invoice is issued.

**What's the difference between reserved and on-demand pricing?**

Reserved is a flat monthly rate. Hourly is the same plan billed by the hour, up to that monthly cap. The AWS Mumbai comparison on each row is the matched price, not a separate discount.

**Are there any egress or bandwidth fees?**

Traffic inside a VPC is ₹0/GB. Tenant bandwidth is 1 Gbps shared. A NAT gateway is a flat monthly charge, with no per-GB processing surcharge. L3/L4 DDoS protection and one IPv4 are included.

**Is DDoS protection really included on every plan?**

Yes. Always-on L3/L4 mitigation is standard on every VPS and VM, including the Starter tier - never a paid add-on.

**Which region are servers deployed in?**

The live region is Noida (ap-south-3). Mumbai is announced and is not deployable. Data stays in Noida. Consent, purpose and retention under the DPDP Act stay with the application.

**Can I cancel anytime?**

Yes. There are no long-term contracts - destroy an instance whenever you like and billing stops. Hourly instances are billed only for the time they run.

## Key pages

- Pricing: https://www.datadack.cloud/pricing?from=llms-full
- Cost calculator: https://www.datadack.cloud/pricing/calculator?from=llms-full
- All products: https://www.datadack.cloud/products?from=llms-full
- Provider comparisons: https://www.datadack.cloud/alternatives?from=llms-full
- DPDP Act and data residency: https://www.datadack.cloud/dpdp-act?from=llms-full
- System status: https://www.datadack.cloud/status?from=llms-full
- Looking glass: https://www.datadack.cloud/looking-glass?from=llms-full
- Contact: https://www.datadack.cloud/contact?from=llms-full