AWS Snowball Edge is no longer available to new customers, according to AWS’s current API documentation. If you are evaluating a large data move today, the practical question is which AWS-named alternative fits your data, network and deadline. If you already hold an AWS account, the question is whether your account and Region can still order a device. This guide covers both, then explains how the Snowball Edge job model worked so you can judge any transfer plan you are handed.
What the availability change means
The clearest statement comes from AWS’s Snowball Edge API Reference, on the CreateJob page: “AWS Snowball Edge is no longer available to new customers.” Read it as the starting point for any plan. It does not tell you whether a specific existing account, or a specific AWS Region, can still create a job. AWS’s documentation does not resolve that question for existing customers, so confirm eligibility with AWS directly (through the account console or your AWS account team) before you schedule a project around a device.
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Because of that, treat any older internal runbook, blog post or quote that assumes a Snowball Edge order as needing re-verification.
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Snowball Edge was an AWS-managed device used through a job workflow. You did not buy it. AWS prepared and shipped a device for a job, you moved data to or from it locally, and you returned it to AWS for processing. The Snowball Edge client, which handles the transfer, is downloadable software that you installed on a workstation you owned. AWS’s documentation asks for a powerful workstation, but it does not prescribe a specific computer model, and no particular accessory was part of the service.
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That distinction matters when comparing options. Snowball Edge was a physical transfer service tied to a job. It was not a general storage appliance, and it should not be confused with online transfer services.
The three Snowball Edge job types
AWS described three job types. Each one serves a different direction of data movement or a different on-premises purpose.
| Job type | Direction | Capacity per device or job part (AWS figure) | Key detail |
|---|---|---|---|
| Import job | Local data into Amazon S3 | Up to 210 TB; one device per job | Covers 210 TB or less per job |
| Export job | Amazon S3 data to an on-premises destination | Up to 210 TB per job part; one device per part | AWS can split a large export into multiple job parts |
| Local compute and storage job | Stays on-premises | Single device or cluster; capacity not stated in this table | Does not complete by importing the local data into S3 |
Import jobs
Import is the most common use case: you have data on local storage and want it in S3. Each import job is tied to one device, so a dataset larger than 210 TB needs more than one job.
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Export jobs
Export moves objects out of S3 to a destination you control on-premises. Because a single export can be split into job parts, plan the number of parts before you create the job so the schedule matches your destination storage.
Local compute and storage jobs
These jobs run workloads on the device itself, or on a cluster of devices, at the edge. The data does not move into S3 at the end, so do not use this job type as a bulk migration route.
The import workflow, step by step
- Create the job in the Snow Family Management Console, or through the job management API.
- Wait for AWS to prepare the device. AWS documents preparation taking up to four weeks.
- When the device arrives, obtain the manifest and unlock code for the job, and install the Snowball Edge client on your own workstation.
- Connect the device to the local network and transfer files through the S3 adapter or NFS interface.
- Return the device to AWS using the shipping details for the job.
- AWS imports the data into S3. After the job completes, AWS states that it erases the device to the NIST 800-88 standard.
Export jobs follow the same logic in reverse: AWS prepares the device with the S3 data, you copy it to your destination, and the device is returned.
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Plan the whole schedule, not only the transit
The most common scheduling error is to count only shipping time. A job has several phases, and only some of them are controlled by the shipping speed you pick.
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|---|---|---|
| Device preparation | AWS workflow after job creation | Up to four weeks |
| Outbound transit | Shipping speed selected for the job | Speed describes transit time, not the interval from job creation to arrival |
| Local transfer | Network configuration, file sizes, local server read speed | Not stated as a fixed figure; depends on your environment |
| Return transit | Return shipping | Not stated as a fixed figure in the reviewed documentation |
| AWS processing | Import or export handling at AWS | Not stated as a fixed figure in the reviewed documentation |
Do not promise a delivery date from the shipping speed alone. Build the schedule from the full chain of phases, and leave margin for the phases AWS does not quantify.
Sizing the job from measured conditions
Start with the actual size of your data, not the device label. AWS documents usable capacity of approximately 39.5 TB or 210 TB, depending on device type. Confirm which device type applies to your job before you calculate how many devices you need.
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For imports above 500 TB, AWS documents a large data migration planning feature, described in its large data migration plan documentation. Use that planning path rather than stacking standard jobs by hand.
Throughput is the other half of the estimate. A simple check is to divide your total data volume by the number of days you can allow for local transfer. That gives the sustained rate your environment must deliver. AWS’s migration guide includes a planning example of a 300 TB transfer over 10 days at 250 MB/s, which uses two devices with 210 TB storage. Treat that as an illustration of the method, not a benchmark. Your achievable rate depends on your network, your file sizes and how quickly your local storage can be read.
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Several AWS limits can invalidate a plan that looks sound on paper. Check each one against your data.
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- Plug-and-play expandability
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- Static files. Files modified while they are being transferred are not imported. Freeze the source data or stage a consistent copy first.
- Multipart parts. Multipart transfer parts have a 2 GiB maximum.
- Jumbo frames. AWS documents that jumbo frames are unsupported, so do not assume your network’s jumbo frame settings will carry through.
- Trailing slashes. Exported objects whose names end in a slash are not transferred unless you change the names.
- Completion window. Jobs generally must be completed within 360 days of device preparation. After that, the device becomes locked and must be returned.
- Encryption. AWS documents SSE-S3 and SSE-KMS support. SSE-C is documented for Amazon S3 compatible storage on local compute and storage jobs.
- Shipping geography. A device is used in the Region where it is ordered. AWS’s limits documentation says it does not ship between non-US Regions, or to an address in a different country from the one specified at job creation.
Confirm the current figures in the AWS quotas and limits documentation before you finalize, because these limits are the ones most likely to change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.AWS-named alternatives
AWS names several alternatives for customers who cannot use Snowball Edge. They serve different transfer modes, so compare them by mode first.
| Option | Transfer mode | Where AWS names it | What to verify |
|---|---|---|---|
| AWS DataSync | Online transfer over the network | Named as the online transfer alternative for new customers | Achievable network throughput, file sizes, and the total transfer window. Pricing: not stated in the reviewed documentation |
| Data Transfer Terminal | Secure physical transfer | Named as the secure physical transfer alternative for new customers | Regional availability and shipping-country limits for your site. Pricing: not stated in the reviewed documentation |
| AWS Partner solutions | Depends on the partner solution | Named as an alternative for new customers | Which transfer modes and regions each partner covers. Scope: not stated at the category level |
| AWS Outposts | Edge computing | Named for edge computing | Whether it fits your workload. AWS does not present it as a bulk data transfer route in the reviewed material |
The sources do not establish a universal best option, current comparative pricing, or performance guarantees. A ranking would need data specific to your region, workload and network, so use the criteria below rather than a generic winner.
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Record these inputs before you pick a mode:
- Data volume and direction: how much data, and whether it moves into or out of AWS.
- Achievable throughput: measured network speed and local read speed, not the advertised line rate.
- Deadline and schedule: preparation and transit lead time, local copy time, return processing and the project date.
- Access and geography: your account’s eligibility, your AWS Region, shipping-country restrictions and local availability.
- Support needs: whether your team can run the transfer or needs help from an AWS Partner.
Verification checklist before you commit
- Written confirmation that your account and Region can order the service you choose.
- A measured sustained transfer rate, with the required rate calculated from your deadline.
- A confirmed device type, device count and, for exports, the number of job parts.
- A source-data freeze plan, plus a check for file names ending in slashes and for files larger than the multipart limit.
- A schedule that includes preparation, both transit legs, local copy time and AWS processing.
- The destination country and Region confirmed against the job’s shipping limits.
- A completion date inside the 360-day window from device preparation.
If any item cannot be confirmed, resolve it with AWS or an AWS Partner before the project is committed to a date.
Where the figures come from
The figures in this guide are operational limits and planning values from AWS documentation, not independent study results. AWS documentation was reviewed in 2026. The sources reviewed did not include publication dates for the individual pages, so re-check the live documentation before you rely on any number.
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