Oracle Cloud Infrastructure prices data egress at $0.0085 per GB after a 10 TB free monthly allowance, against AWS at roughly $0.09 per GB, a gap of about 90 percent that decides most high-transfer and Oracle-database workloads in OCI's favor, while AWS still wins on service breadth, managed-service depth, and ecosystem. The list rates are close on raw compute, so the real cost difference comes from egress, database licensing, and how each vendor structures its commitment program. This comparison sets out the 2026 numbers across compute, storage, egress, and database, and gives an explicit rule for which cloud fits which workload.
Inside This Guide
How to compare two clouds honestly
A cloud bill is the sum of compute, storage, data transfer, managed services, and support, and the two vendors weight those components very differently. AWS publishes thousands of services and competes on depth, so a like-for-like comparison has to fix the workload first, then price the same shape on each platform. Comparing a headline vCPU rate alone is the fastest way to reach a wrong conclusion, because egress and database terms routinely move the total by more than the compute line does.
The fair method is to model a complete workload: a fixed number of cores and memory, a defined storage footprint, a realistic monthly egress volume, and the database license that sits on top. Price that whole bundle on each cloud at list, then again under each vendor commitment program. Our cloud contracts guide sets out that modeling discipline, and the software licensing advisory service runs it for live deals.
Compute: shapes and on-demand rates
On raw compute the two clouds are closer than their marketing suggests. A general-purpose core costs broadly the same on each at on-demand list, and both offer flexible shapes that let you dial cores and memory independently. OCI emphasizes its flexible shapes, where you pay only for the cores and gigabytes configured, while AWS prices fixed instance families with per-second billing. The table compares representative general-purpose on-demand rates in 2026.
| Compute element | AWS (general purpose) | Oracle Cloud Infrastructure |
|---|---|---|
| Per vCPU / hour, on-demand | ~$0.040 to $0.048 | ~$0.030 to $0.040 (flexible shape) |
| Per GB memory / hour | Bundled in instance | ~$0.0015 (flexible shape) |
| Billing granularity | Per second | Per second |
| Free tier | 12-month limited | Always-free tier plus trial credits |
| Shape flexibility | Fixed families plus some flex | Fully flexible OCPU and memory |
The practical read is that OCI tends to land 10 to 30 percent below AWS on equivalent general-purpose compute at list, largely because its flexible shapes avoid the overprovisioning that fixed families force. AWS closes or reverses that gap on specialized instances, GPU fleets, and Graviton, where its custom silicon and scale give it a genuine price-performance lead. For broad multi-cloud context see our AWS, Azure, and GCP comparison.
Egress: the decisive line item
Data egress is where the two clouds diverge most, and it is the single line that most often decides the platform. OCI gives 10 TB of free outbound transfer each month, then charges about $0.0085 per GB. AWS gives 100 GB free, then charges around $0.09 per GB on a sliding scale that only falls at very high volume. For a workload moving tens of terabytes a month, that difference compounds into a six-figure annual gap on transfer alone.
| Monthly egress | AWS estimated cost | OCI estimated cost | Annual difference |
|---|---|---|---|
| 5 TB | ~$460 | $0 (within free 10 TB) | ~$5,500 |
| 25 TB | ~$2,300 | ~$130 | ~$26,000 |
| 100 TB | ~$8,600 | ~$780 | ~$94,000 |
| 500 TB | ~$40,000 | ~$4,260 | ~$429,000 |
The egress math that moves deals: On 100 TB a month of outbound transfer, AWS bills roughly $8,600 while OCI bills about $780, a yearly gap near $94,000 before any other line item. For data-heavy, content-delivery, or analytics-export workloads, egress alone can justify placing the workload on OCI even if compute is marginally pricier.
Block, object, and storage cost
Storage list rates are competitive on both clouds, with the difference again hiding in the performance tiers and the request charges rather than the headline per-gigabyte price. OCI block volume pricing bundles a baseline performance level and charges separately for higher IOPS, while AWS prices its gp3 and io2 tiers with distinct throughput and IOPS line items. Object storage sits in the same range per gigabyte, but AWS layers request and retrieval charges that OCI structures more simply.
For most workloads storage is a secondary factor next to egress and database, but high-IOPS database storage and large object stores with heavy request volume are worth modeling in detail, because the request and throughput charges can rival the capacity charge. Treat storage as a workload-specific calculation, not a headline rate.
Database licensing and BYOL
Database licensing is the reason many Oracle-heavy estates land on OCI regardless of compute price. Oracle license-included rates and the bring-your-own-license terms are structured to favor running Oracle Database on Oracle's own cloud, where the core factor and the conversion of on-premise licenses are most generous. Running Oracle Database on AWS is fully supported, but the licensing terms are less favorable and the core-counting rules raise the effective cost.
This is a licensing decision before it is an infrastructure decision, and it interacts directly with any Oracle audit exposure. Before committing an Oracle workload to either cloud, confirm how existing licenses convert and what the support position is, a question our OCI pricing reference and the Oracle practice address. For non-Oracle databases the calculus flips, and AWS managed database services often win on operational depth.
Commitment programs compared
Both clouds discount in exchange for spend commitment, and the structures differ. AWS uses the Enterprise Discount Program for a multi-year total-spend commitment plus Savings Plans and Reserved Instances for compute, layering an account-wide discount on top of resource-level reservations. OCI uses Universal Credits and an Annual Universal Credit commitment that applies a single discount across services, with a simpler model that is often easier to forecast.
| Program element | AWS | Oracle Cloud Infrastructure |
|---|---|---|
| Account-wide commit | Enterprise Discount Program | Annual Universal Credits |
| Compute reservation | Savings Plans, Reserved Instances | Capacity reservations |
| Typical commit discount | ~10 to 25% on committed spend | ~10 to 30% on annual commit |
| Forecasting difficulty | Higher, multiple overlapping levers | Lower, single credit pool |
| Overage handling | On-demand list above commit | On-demand list above commit |
The AWS model rewards sophisticated buyers who actively manage reservations, while the OCI model rewards predictability. Neither program is a substitute for getting the workload placement right first, because a discount on the wrong cloud rarely beats list on the right one. Our AWS EDP negotiation guide and the AWS enterprise agreement pillar cover the AWS side in full.
Put together, these four costs explain why two clouds with similar published rate cards can produce real bills that differ by 20 percent or more on the very same workload. The discipline is to model support, internal transfer, lock-in, and migration alongside compute and egress, so the comparison reflects the bill you will actually pay rather than the quote you were handed. A complete model is the only basis on which the verdict below holds.
Side-by-side decision matrix
| Factor | AWS | Oracle Cloud Infrastructure |
|---|---|---|
| General-purpose compute | Competitive, strong on custom silicon | 10 to 30% cheaper at list |
| Egress | Expensive above free tier | Up to 90% cheaper |
| Service breadth | Widest in the market | Narrower, focused |
| Oracle Database | Supported, costlier license terms | Most favorable license terms |
| Managed services | Deepest ecosystem | Fewer, improving |
| Commitment model | Complex, powerful for active buyers | Simple, predictable |
| Best for | Broad, service-rich, non-Oracle estates | Oracle workloads and egress-heavy loads |
The verdict: choose which when
Choose Oracle Cloud Infrastructure when the workload is Oracle Database-centric, when monthly egress runs into the tens of terabytes or more, or when predictable, simple commitment pricing matters more than service breadth. The egress and Oracle-license advantages are large enough to overcome AWS depth for these specific profiles, and they are the cases where OCI is not merely competitive but clearly cheaper.
Choose AWS when the workload needs the widest range of managed services, depends on a deep ecosystem, runs on custom silicon like Graviton, or spans many non-Oracle databases and analytics tools. AWS breadth and price-performance on specialized compute outweigh the egress premium for most general enterprise estates, particularly those already standardized on its tooling.
The practical rule: Model the complete workload, not the vCPU rate. If it is Oracle-database-heavy or egress-heavy, OCI usually wins on total cost. If it needs service breadth and ecosystem depth, AWS usually wins despite higher egress. The right answer for a large estate is often both clouds, each holding the workloads it prices best.
Support, SLA, and hidden costs
The rate card is only part of a cloud bill, and three costs beyond it routinely change the comparison. Support is the first. AWS sells tiered support, with Business and Enterprise plans priced as a percentage of monthly spend that can add 3 to 10 percent to the total, while OCI includes a baseline level of support in its pricing and charges less for elevated tiers. On a large estate the AWS support percentage alone can rival a meaningful slice of the compute saving, so it belongs in any honest model.
The second hidden cost is inter-region and inter-availability-zone transfer. Both clouds charge for moving data between regions, and AWS additionally charges for traffic between availability zones inside a region, which surprises teams that architect for resilience across zones. A multi-zone, multi-region design that looks identical on paper can cost materially more on one cloud than the other once this internal transfer is priced, and it is easy to miss because it does not appear in a simple compute-plus-storage estimate.
The third is the cost of managed-service lock-in. A workload built on a deep AWS managed service is cheaper to run there but expensive to move, while a workload kept portable on standard compute and open formats preserves the ability to place it on the cheaper cloud later. That portability has a real option value that rarely shows up in a first-year quote but determines how much negotiating power you keep at the next renewal.
Migration cost is the fourth factor, and it is one-time rather than recurring. Moving an established estate between clouds carries real engineering effort, retraining, and a period of parallel running, so a cheaper destination cloud only wins once the saving clears the switching cost over the planning horizon. For an Oracle-heavy estate facing an Oracle audit, the licensing saving on OCI often clears that bar quickly, while a general estate already deep in AWS tooling usually does not, which is why workload-by-workload placement beats a wholesale migration for most organizations.