Raff vs Google Cloud Compute Engine: 2026 Comparison

Introduction

Raff vs Google Cloud Compute Engine is a comparison between two very different cloud buying models. Raff is built around simple, published virtual machine pricing with included NVMe storage and unmetered bandwidth. Google Cloud Compute Engine is one part of a much larger hyperscaler platform with dozens of compute families, 43 global regions, global networking primitives, and a deep surrounding ecosystem of managed services.

That difference matters immediately. If your team mainly wants virtual machines, storage, networking, backups, and straightforward monthly economics, Raff is the simpler product to understand and budget. If you need a very broad platform with managed Kubernetes, managed databases, global load balancing, advanced networking, and hyperscaler-scale regional choice, Google Cloud naturally has the advantage.

This comparison focuses on what a real buyer actually needs to know in 2026: how pricing behaves, what is included in the advertised VM price, where Google’s platform depth creates genuine value, and where Raff’s tighter infrastructure-first approach is a better fit. Because Google’s VM catalog is very broad, the pricing table in this article uses Google C4 Standard Linux on-demand pricing in Iowa (us-central1) as a premium performance-class baseline and converts hourly prices to monthly equivalents using 730 hours.

Raff Overview

Raff VM is designed around a much tighter infrastructure proposition: virtual machines, storage, data protection, private networking, and core cloud building blocks without the sprawl of a hyperscaler catalog.

That focus shows up in the pricing model and in what is already included. Raff’s public CPU-Optimized line starts at $3.99/month for 1 vCPU, 1 GB RAM, and 25 GB NVMe SSD, then scales through $9.99 for 1 vCPU / 2 GB, $19.99 for 2 vCPU / 4 GB, $36.00 for 4 vCPU / 8 GB, and $64.00 for 8 vCPU / 16 GB. Existing Raff comparison pages also describe that line as AMD EPYC-based with NVMe storage, IPv4 and IPv6, DDoS protection, private networking, and unmetered bandwidth. That is a very different starting point from a platform where compute, disks, and egress are all broken into separate charges.

Raff’s public site also leans heavily into operational simplicity: deploy in seconds, unmetered bandwidth, included base storage, and a US-focused infrastructure footprint rather than a globally distributed hyperscaler map. Its current public pricing and product pages also show 14-day money-back guarantee language and position items like Kubernetes and Raff Apps as “Soon,” which is useful context when comparing current breadth versus direction of travel.

So the practical frame for Raff is straightforward: it is the better fit when you want infrastructure that is easier to price, easier to explain internally, and less likely to surprise a smaller team with layered billing complexity. That is especially relevant if your workload does not need a large managed-service estate.

Google Cloud Compute Engine Overview

Google Cloud Compute Engine is an Infrastructure-as-a-Service VM platform inside one of the deepest cloud ecosystems in the market. Google describes Compute Engine as flexible, self-managed virtual machines running on Google infrastructure, integrated with the rest of Google Cloud. It also notes that each Compute Engine vCPU is implemented as a hardware hyper-thread, which is a useful reminder that Google’s VM catalog is built for enormous flexibility across many families rather than one fixed performance story.

That broader platform is where Google clearly pulls ahead. Google Cloud’s current public infrastructure page lists 43 regions, 130 zones, and 200+ network edge locations. Its load balancing platform includes global application load balancing, a single IP for a global audience, and multi-region HTTP(S) distribution. Beyond VM compute, Google also has GKE for managed Kubernetes, Cloud SQL for managed relational databases, Cloud Storage for object storage, and Cloud Armor for DDoS and WAF capabilities layered around load-balanced applications.

That is what makes this comparison less about “which provider is more powerful?” and more about “how much platform do you actually need?” Google Cloud is obviously stronger on scope. The question is whether that scope is necessary for your workload and team.

Pricing Comparison

Pricing is where the operational difference becomes easiest to see.

For this article, I used Google’s public C4 Standard Linux on-demand pricing in Iowa (us-central1) as the premium performance-class baseline. Google’s public pricing page shows c4-standard-2 at $0.096866/hour, c4-standard-4 at $0.19767/hour, c4-standard-8 at $0.39534/hour, and c4-standard-16 at $0.79068/hour. At 730 hours per month, that works out to roughly $70.71, $144.30, $288.60, and $577.20 per month respectively — and that is compute only, before persistent disks and networking.

Against that, Raff’s published CPU-Optimized pricing is far simpler to read. The overlapping performance classes currently come in at $19.99/month for 2 vCPU / 4 GB / 80 GB NVMe, $36.00/month for 4 vCPU / 8 GB / 120 GB NVMe, $64.00/month for 8 vCPU / 16 GB / 180 GB NVMe, and $256.00/month for 16 vCPU / 64 GB / 480 GB NVMe. On price clarity alone, Raff is easier for a small or mid-sized team to budget.

That does not mean “Google is overpriced” in some absolute sense. It means Google is packaging compute inside a much larger platform model. If you need that platform depth, the higher VM cost can be rational. If you mainly want VMs and supporting cloud primitives, the gap becomes much harder to justify.

Feature Comparison

Feature comparison is where the “better value” answer becomes more nuanced.

Both providers cover the core infrastructure layer: virtual machines, snapshots, block storage, private networking, APIs, CLI-driven workflows, and image-based provisioning. Google Compute Engine supports custom images and snapshots directly, and Google Cloud VPC provides a global, scalable networking model. Raff also supports custom images, data protection workflows, and infrastructure-focused services like Data Protection, Object Storage, and Load Balancers.

The separation becomes clear one layer above that core. Google has live, mature managed offerings across Kubernetes, relational databases, object storage, and advanced security services. Raff is currently much more focused: strong VM economics, simpler cloud primitives, and a platform that stays closer to the infrastructure layer. That is not a weakness if your workload lives mostly at that layer. It is a real limitation if you want a hyperscaler platform instead of a focused VM cloud.

Compute & Performance

Compute comparison is tricky because Google has many VM families: cost-oriented, general-purpose, performance-focused, compute-optimized, memory-optimized, and more. On its pricing page, Google explicitly separates E2 as the lowest-cost-per-core option from more advanced performance families like C4 and C3. That means there is no single “Google VM price” any more than there is a single “AWS VM price.” That is why I chose C4 Standard for the main table here. If you are comparing Raff’s CPU-Optimized tiers to a premium, current, performance-oriented Google family, C4 is a cleaner apples-to-apples basis than Google’s cheaper E2 line. The trade-off is that Google’s C4 standard sizes also come with more RAM than Raff’s lower CPU-Optimized tiers at the same vCPU count.

So the fair takeaway is not “Raff always beats Google on compute.” The fair takeaway is this:

• Raff is materially cheaper for straightforward performance-class VM hosting.
• Google gives you much more family choice, tuning flexibility, and surrounding platform depth.
• Google’s public compute pricing is harder to reduce to a single simple number because the catalog is built for many workload types.

If your team wants predictable VM economics first, Raff wins this category more often. If your team wants a hyperscaler catalog with many instance families and advanced placement options, Google is naturally stronger.

Networking

Networking is one of Google Cloud’s clearest strengths.

Google Cloud VPC is explicitly described as global, scalable, and flexible, and Google’s public network pricing pages make it very clear that networking is part of the cost model, not a free included assumption. Premium Tier is the default network tier, same-zone internal traffic inside the same VPC can be free, same-region inter-zone VM traffic can cost $0.01/GiB, and broader inter-region or internet data transfer is separately priced.

Google also has a stronger load balancing story than Raff today. Its public load balancing platform supports global application load balancing, a single global IP, multi-region HTTP(S) balancing, and deeply integrated security and traffic-management capabilities. This is one of the real reasons teams choose Google Cloud: not because a single VM is cheap, but because the network architecture options are much broader.

Raff’s networking story is much simpler and, for many smaller teams, much easier to like. Unmetered bandwidth is a real differentiator because it removes one of the most annoying and uncertainty-heavy line items in cloud budgeting. If you are running developer tooling, apps, websites, APIs, or workloads where you simply do not want to think about outbound transfer pricing all the time, Raff’s simpler networking economics are genuinely useful.

Storage & Data Protection

Google Cloud is stronger on storage-service breadth. Cloud Storage is a mature global object storage service, and Cloud SQL gives Google an immediately stronger managed database story. Compute Engine snapshots are also first-class: Google’s current docs state that you can create snapshots from disks while they are attached to running instances and use them to restore data to new disks or VMs.

Raff, however, is stronger on pricing clarity and infrastructure packaging at the VM layer. Its current public Data Protection pages describe instant snapshots, automated backups, adjustable retention, rapid recovery, and multi-node replication with very legible pricing language. For teams that do not need Google’s full storage-and-database ecosystem, that kind of clarity is often more valuable than having a longer service catalog.

This becomes a recurring theme in the whole comparison: Google wins on platform scope, Raff wins on infrastructure focus and easier economic reasoning.

Platform & Ecosystem

This is the section where Google Cloud clearly dominates.

GKE is fully managed Kubernetes. Cloud SQL is fully managed MySQL, PostgreSQL, and SQL Server. Cloud Storage is full-scale object storage. Cloud Armor adds a stronger WAF and DDoS layer at the edge of Google’s network. And all of that sits inside a cloud platform with 43 regions, broad IAM tooling, marketplace software, and an enormous surrounding ecosystem.

Raff cannot honestly compete with Google on that dimension today.

What Raff offers instead is a much more focused infrastructure operating model: Raff VM, Object Storage, Data Protection, networking, and a product line that stays close to the needs of smaller teams, agencies, developers, and infrastructure buyers who do not want hyperscaler sprawl.

That makes the platform question fairly simple:

• If you need broad managed services and global-scale platform options, Google wins.
• If you want a simpler cloud foundation that covers the infrastructure layer well, Raff is often the better fit.

Billing, Entry Cost, and Buying Experience

Google bills VM compute with a 1-minute minimum and then per-second increments, which is flexible, but its pricing model still requires you to think about multiple separate components. Google also pushes users toward calculators, consumption models, flexible CUDs, resource CUDs, disk pricing, and networking pricing. That is powerful, but it is not simple. Google also advertises $300 in free credits plus always-free products, which is a very strong entry path for experimentation.

Raff’s buying experience is less sophisticated, but more direct. The public site emphasizes from-$3.99/month entry pricing, unmetered bandwidth, included NVMe storage, fast deployment, and a 14-day money-back guarantee. That is a much easier story for a small team, agency, or startup that wants to know “what does a working VM platform cost me?” rather than “how do I model a hyperscaler bill correctly?”

Who Should Choose Raff?

Choose Raff if you want:

• straightforward published VM pricing
• included NVMe base storage
• unmetered bandwidth
• smaller-team simplicity
• a US-focused infrastructure story
• core IaaS building blocks without hyperscaler sprawl

Raff is especially strong for developers, agencies, internal tools, staging environments, customer workloads that mainly need virtual machines, and teams that do not want egress pricing to become a recurring finance conversation.

Who Should Choose Google Cloud Compute Engine?

Choose Google Cloud Compute Engine if you want:

• 43-region global reach
• much deeper managed-service breadth
• GKE, Cloud SQL, and Cloud Storage under one umbrella
• global load balancing and stronger advanced networking
• enterprise-scale architecture flexibility
• a hyperscaler ecosystem you can keep expanding into

Google is the better fit when your VM decision is really part of a much broader cloud-platform decision.

Conclusion

Raff vs Google Cloud Compute Engine is not a close call if the question is platform breadth. Google Cloud wins easily there.

The more useful question is whether you actually need that breadth.

If you mainly need VMs, storage, backups, networking, and infrastructure you can price and reason about cleanly, Raff is the better-value choice. Its published CPU-Optimized VM line is materially cheaper on the premium performance-class comparison used here, includes storage, and avoids the default egress-metered economics that make hyperscaler bills harder to predict.

If you need a global hyperscaler platform with managed Kubernetes, managed databases, global load balancing, advanced security tooling, and region-level flexibility, Google Cloud Compute Engine is the stronger long-term fit.

So the practical guidance is simple:

• Choose Raff for simple VM economics, included bandwidth, and smaller-team cloud infrastructure.
• Choose Google Cloud for global scale, platform depth, and managed-service breadth.

If you are evaluating more hyperscaler alternatives, the next logical reads are Raff vs Azure Virtual Machines, Raff vs Oracle Cloud, and Raff vs DigitalOcean.