Google Cloud Migration Cost Calculator — True Cost of Migrating to GCP (2026)

Cloud Migration Cost Estimator

Independent · No lead forms · Updated 2026

Migration Source

Target Cloud

Servers / VMs100

1500

Data Volume20 TB

1 TB500 TB

Migration Strategy

Timeline12 months

2 months36 months

Total Project Cost Estimate

$1.7Mtypical

Range: $931K–$2.7M

Low: $931KHigh: $2.7M

Monthly Cloud Cost

$60K

post-migration

Break-Even

86 mo

from go-live

Monthly Savings

+$20K

vs on-premise

Data Egress Cost

$2K

one-time transfer

Cost Breakdown

Migration Labour$1.4M

Parallel Running$1.4M

Egress / Data Transfer$2K

Tooling & Assessment$20K

Contingency (20%)$284K

Estimates based on 2026 market rates. Actual costs vary by workload complexity, geographic region, and negotiated contract terms. Add 20–40% contingency for hidden costs.

Top Cost Drivers for This Scenario

1. Migration labour ($1.4M) · 2. Parallel running ($1.4M) · 3. Egress costs ($2K)

GCP

GCP's Automatic Sustained-Use Discounts

Unlike AWS Reserved Instances (which require 1–3 year upfront commitments) or Azure Reserved VMs, GCP applies compute discounts automatically based on usage — no commitment required. This is GCP's biggest cost advantage for compute workloads.

25% of month

No discount yet

50% of month

10%

Automatic

75% of month

20%

Automatic

100% of month

30%

Full sustained-use

* Applies to Compute Engine N1, N2, C2 instance families. Custom machine types also eligible. Does not apply to preemptible/spot instances (already discounted).

GCP Cost Components

GCP-specific costs

Google Cloud Migrate

Free

Formerly Velostrata. Google Cloud Migrate (for VMs) handles lift-and-shift replication. No per-server fees for the tool.

Egress to GCP

First 200GB free, then $0.08/GB

GCP offers 200GB free egress per month, better than AWS (no free tier) or Azure (100GB free). 50TB migration: ~$4,096.

Committed Use Discounts

Save 37–55% on compute

1-year committed use discounts save 37% on memory-optimised instances. 3-year saves 55%. Combine with sustained-use discounts for maximum savings.

GCP Support Plans

Standard: $150/month minimum

Enhanced Support: $500/month or 3% of monthly spend. Premium Support (enterprise SLA): custom. More competitive than AWS for mid-market customers.

GCP Professional Services

$150–$300/hour

Google Cloud PS rates are slightly lower than AWS PS. However, fewer GCP Partners exist than AWS or Azure — which can make it harder to find qualified GCP consultants.

Fit Assessment

Who should choose GCP?

Data / Analytics / ML Teams

Strong fit

BigQuery is the most cost-effective data warehouse in the market — $5/TB queried on-demand, with no infrastructure to manage. Vertex AI unifies ML workflows. If data is your primary workload, GCP is the clear choice.

Kubernetes-First Organisations

Strong fit

Google invented Kubernetes. GKE has the deepest integration, most mature feature set, and best operational tooling. If you're running container workloads at scale, GKE outperforms EKS and AKS on management overhead.

Cost-Sensitive Compute Workloads

Good fit

For compute workloads with steady-state usage (>50% of month), GCP's sustained-use discounts provide 10–30% cheaper compute than equivalent AWS/Azure on-demand without any upfront commitment.

Microsoft-Heavy Environments

Poor fit

If you run significant Windows Server, SQL Server, or Active Directory workloads, Azure's Hybrid Benefit makes Azure substantially cheaper. GCP has limited Windows licensing optimisations.

GCP Egress by Data Volume

Volume	Rate / GB	Total
1 TB	$0.08	$82
10 TB	$0.08	$820
50 TB	$0.08	$4K
150 TB	$0.06	$9K
300 TB+	$0.05	negotiated

Data Workloads

BigQuery migration cost

Migrating data warehouse workloads to BigQuery is often GCP's strongest use case. Here's the cost breakdown for a typical on-premise data warehouse migration.

$20K–$60K

Migration to BigQuery (replatform)

ETL pipeline migration, schema conversion, query optimisation

$60K–$200K

Migration to BigQuery (full refactor)

Full modernisation with Dataflow, Pub/Sub, Vertex AI

$5/TB queried

BigQuery on-demand pricing

No infrastructure. No reserved capacity needed for <10TB/month

$1,700–$2,500/mo

BigQuery reserved capacity

For > 10TB/month queries. Flat rate, predictable billing.

Free tier available

Looker Studio integration

Replace on-premise BI tools. Looker (GCP native) for enterprise.

30–60% cost reduction

Typical ROI vs on-premise DWH

No hardware refresh, elastic scaling, auto-managed storage.

GCP FAQ

GCP migration questions answered

Is GCP cheaper than AWS for cloud migration?+

GCP is typically 10–30% cheaper than AWS for compute-heavy workloads, primarily due to sustained-use discounts (automatic 30% discount after 25% monthly usage — no reservation needed). However, GCP has a smaller partner ecosystem, meaning consulting costs for GCP migrations may be higher than AWS. The migration itself costs roughly the same across providers.

What is Google Cloud sustained-use discount and how does it work?+

Sustained-use discounts (SUDs) are automatic discounts for running GCP Compute Engine instances for more than 25% of a month. You get a 20% discount at 50% usage, and up to 30% discount at 100% monthly usage. Unlike AWS Reserved Instances or Azure Reserved VMs, there's no upfront commitment required — discounts apply automatically.

Who should choose GCP for cloud migration?+

GCP is the best fit for: (1) Data/analytics/ML teams — BigQuery, Vertex AI, and Dataflow are GCP's strongest differentiators; (2) Kubernetes-first teams — GKE is the most mature managed Kubernetes service; (3) Cost-sensitive compute workloads that can benefit from sustained-use discounts without upfront commitments.

How much does migrating a data warehouse to GCP cost?+

Migrating a data warehouse to BigQuery on GCP typically costs $60,000–$200,000 for a full refactor, or $20,000–$60,000 for a replatform. BigQuery eliminates the need for dedicated warehouse infrastructure — queries are billed at $5/TB processed (on-demand) or $1,600–$2,400/month for reserved capacity. Most organisations see 30–60% cost reduction vs on-premise data warehouse infrastructure.