AWS Snowball
User Guide

This guide is for the Snowball (50 TB or 80 TB of storage space). If you are looking for documentation for the Snowball Edge, see the AWS Snowball Edge Developer Guide.

Performance for AWS Snowball

Following, you can find information about AWS Snowball performance. Here, we discuss performance in general terms, because on-premises environments each have a different way of doing things—different network technologies, different hardware, different operating systems, different procedures, and so on.

The following table outlines how your network's transfer rate impacts how long it takes to fill a Snowball with data. Transferring smaller files without batching them into larger files reduces your transfer speed due to increased overhead.

Rate (MB/s) 42-TB Transfer Time 72-TB Transfer Time
800 14 hours 1 day
450 1.09 days 1.8 days
400 1.16 days 2.03 days
300 1.54 days 2.7 days
277 1.67 days 2.92 days
200 2.31 days 4 days
100 4.63 days 8.10 days
60 8 days 13 days
30 15 days 27 days
10 46 days 81 days

The following describes how to determine when to use Snowball instead of data transfer over the internet, and how to speed up transfer from your data source to the Snowball.

Speeding Up Data Transfer

In general, you can improve the transfer speed from your data source to the Snowball in the following ways, ordered from largest to smallest positive impact on performance:

  1. Use the latest Mac or Linux Snowball client – The latest Snowball clients for Mac and Linux both support the Advanced Encryption Standard New Instructions (AES-NI) extension to the x86 instruction set architecture. This extension offers improved speeds for encrypting or decrypting data during transfers between the Snowball and your Mac or Linux workstations. For more information on AES-NI, including supported hardware, see AES instruction set on Wikipedia.

  2. Batch small files together – Each copy operation has some overhead because of encryption. Therefore, performing many transfers on individual files has slower overall performance than transferring the same data in larger files. You can significantly improve your transfer speed for small files by batching them in a single snowball cp command. Batching of small files is enabled by default. During the import process into Amazon S3, these batched files are automatically extracted to their original state. For more information, see Options for the snowball cp Command.

  3. Perform multiple copy operations at one time – If your workstation is powerful enough, you can perform multiple snowball cp commands at one time. You can do this by running each command from a separate terminal window, in separate instances of the Snowball client, all connected to the same Snowball.

  4. Copy from multiple workstations – You can connect a single Snowball to multiple workstations. Each workstation can host a separate instance of the Snowball client.

  5. Transfer directories, not files – Because there is overhead for each snowball cp command, we don't recommend that you queue a large number of individual copy commands. Queuing many commands has a significant negative impact on your transfer performance.

    For example, say that you have a directory called C:\\MyFiles that only contains three files, file1.txt, file2.txt, and file3.txt. Suppose that you issue the following three commands.

    snowball cp C:\\MyFiles\file1.txt s3://mybucket snowball cp C:\\MyFiles\file2.txt s3://mybucket snowball cp C:\\MyFiles\file3.txt s3://mybucket

    In this scenario, you have three times as much overhead as if you transferred the entire directory with the following copy command.

    Snowball cp –r C:\\MyFiles\* s3://mybucket
  6. Don't perform other operations on files during transfer – Renaming files during transfer, changing their metadata, or writing data to the files during a copy operation has a significant negative impact on transfer performance. We recommend that your files remain in a static state while you transfer them.

  7. Reduce local network use – Your Snowball communicates across your local network. Because of this, reducing other local network traffic between the Snowball, the switch it's connected to, and the workstation that hosts your data source can improve data transfer speeds.

  8. Eliminate unnecessary hops – We recommend that you set up your Snowball, your data source, and your workstation so that they're the only machines communicating across a single switch. Doing so can result in a significant improvement of data transfer speeds.

Experimenting to Get Better Performance

Your performance results will vary based on your hardware, your network, how many and how large your files are, and how they're stored. Therefore, we suggest that you experiment with your performance metrics if you're not getting the performance that you want.

First, attempt multiple copy operations until you see a reduction in overall transfer performance. Performing multiple copy operations at once can have a significantly positive impact on your overall transfer performance. For example, suppose that you have a single snowball cp command running in a terminal window, and you note that it's transferring data at 30 MB/second. You open a second terminal window, and run a second snowball cp command on another set of files that you want to transfer. You see that both commands are performing at 30 MB/second. In this case, your total transfer performance is 60 MB/second.

Now, suppose that you connect to the Snowball from a separate workstation. You run the Snowball client from that workstation to execute a third snowball cp command on another set of files that you want to transfer. Now when you check the performance, you note that all three instances of the snowball cp command are operating at a performance of 25 MB/second, with a total performance of 75 MB/second. Even though the individual performance of each instance has decreased in this example, the overall performance has increased.

Experimenting in this way, using the techniques listed in Speeding Up Data Transfer, can help you optimize your data transfer performance.

Performance Considerations for HDFS Data Transfers

When getting ready to transfer data from a Hadoop Distributed File System (HDFS) cluster (version 2.x) into a Snowball, we recommend that you follow the guidance in the previous section, and also the following tips:

  • Don't copy the entire cluster over in a single command – Transferring an entire cluster in a single command can cause performance issues, including slow transfers, "flipped" bits, and missing or corrupted data on the Snowball. We recommend that in this case you separate the data transfer into multiple parts.

  • Don't transfer a large number of small files – Suppose that you have a large number of files, say over 1000, and those files are small, say under 1 MB each in size. In this case, transferring them all at once has a negative impact on your performance. This performance degradation is due to per-file overhead when you transfer data from HDFS clusters.

    If you must transfer a large number of small files, we recommend that you find a method of collecting them into larger archive files, and then transferring those. However, these archives are what is imported into Amazon S3. If you want the files in their original state, take them out of the archives after importing the archives.


The --batch option for the Snowball client's copy command is not supported for HDFS data transfers.