Oracle Cloud vs AWS cost: what to compare

By Rohit Athaide · Published 4 Nov 2026

Short answer: whether Oracle Cloud Infrastructure (OCI) costs less than AWS depends on the workload. The way to find out is to compare the same services in the same region with the same options, line by line. OCI is structured differently from AWS in a few places, and those places are where most of the difference comes from.

Key points

• OCI sells flexible compute shapes where CPU and memory are chosen separately.
• OCI prices compute by OCPU, which is a physical core, not a vCPU.
• Data transfer allowances and rates differ and often decide a web app total.
• Match engine, size, architecture and availability design before comparing databases.
• List prices come first. Discounts are a second step.

How is OCI structured differently from AWS?

• Compute can be sized by the parts. On flexible shapes you pick the number of OCPUs and the amount of memory separately, so you can match a need instead of the nearest fixed size. AWS mostly sells fixed sizes with set CPU and memory. See the vCPU explainer.
• OCPU is not vCPU. One OCPU is one physical core. On x86, which runs two threads per core, an OCPU equals two vCPUs, so Oracle’s per-OCPU price must be halved to compare it with a per-vCPU price. Oracle’s own pricing pages show this comparison.
• Data transfer terms differ. Oracle publishes a monthly free outbound allowance and tiered rates by geography after it. AWS has its own free allowance and tier breaks. Read both pages, since egress often decides a web app total. See data transfer costs and Oracle’s networking pricing.
• Managed databases differ. OCI’s depth is in Oracle Database services. For PostgreSQL, compare against AWS’s managed PostgreSQL using the same engine and the same availability setting. See managed PostgreSQL pricing.

AWS list prices are on its pricing page. Oracle’s are on its price list.

What should I match before comparing?

1. Same CPU architecture, Arm or x86. See Arm or x86.
2. Same memory per core and same disk type.
3. Same availability design: one zone or several. See multi-AZ costs.
4. Same region group, such as Mumbai.
5. List prices first, discounts later.

What does a worked example look like?

Made-up round numbers to show the method, not real prices. A server with 4 vCPUs on AWS against OCI.

The example shows two traps at once. A per-OCPU rate looks twice as high but is not, and a flexible shape adds a separate memory charge that a fixed size hides inside its price. Always convert to the same unit and include every part. Use real figures from the AWS vs Oracle compare page.

Where is the gap real, and where is it not?

Some workloads show a clear difference on list prices, especially data-heavy ones and ones that need a lot of memory. Others come out close, and then the deciding factors are service coverage, tooling, existing skills and support. A service one cloud does not offer shows as a gap in our results, never as free.

Which mistakes make the comparison wrong?

• Treating an OCPU as a vCPU.
• Comparing an Arm shape with an x86 size.
• Leaving out the memory charge on a flexible shape.
• Forgetting the free data-out allowance on one side only.
• Comparing a managed Oracle Database service with an AWS managed PostgreSQL.

Decision checklist

• Are CPU units converted to the same basis?
• Are memory, disk and network matched?
• Is the data-out allowance counted on both sides?
• Is the availability design the same?
• Have I read list prices vs what you actually pay?

Next steps

The AWS vs Oracle compare page lists every price line with its vendor SKU and a link to the vendor’s page. The web app estimator totals a full workload on both. For a three-way view see AWS vs Azure vs Google Cloud pricing.