Is it better to have many small Azure storage blob containers (each with some blobs) or one really large container with tons of blobs?

Question

So the scenario is the following:

I have a multiple instances of a web service that writes a blob of data to Azure Storage. I need to be able to group blobs into a container (or a virtual directory) depending on when it was received. Once in a while (every day at the worst) older blobs will get processed and then deleted.

I have two options:

Option 1

I make one container called "blobs" (for example) and then store all the blogs into that container. Each blob will use a directory style name with the directory name being the time it was received (e.g. "hr0min0/data.bin", "hr0min0/data2.bin", "hr0min30/data3.bin", "hr1min45/data.bin", ... , "hr23min0/dataN.bin", etc - a new directory every X minutes). The thing that processes these blobs will process hr0min0 blobs first, then hr0minX and so on (and the blobs are still being written when being processed).

Option 2

I have many containers each with a name based on the arrival time (so first will be a container called blobs_hr0min0 then blobs_hr0minX, etc) and all the blobs in the container are those blobs that arrived at the named time. The thing that processes these blogs will process one container at a time.

So my question is, which option is better? Does option 2 give me better parallelization (since a containers can be in different servers) or is option 1 better because many containers can cause other unknown issues?

Answer 1

I don't think it really matters (from a scalability/parallelization perspective), because partitioning in Win Azure blobs storage is done at the blob level, not the container. Reasons to spread out across different containers have more to do with access control (e.g. SAS) or total storage size.

See here for more details: http://blogs.msdn.com/b/windowsazurestorage/archive/2010/05/10/windows-azure-storage-abstractions-and-their-scalability-targets.aspx

(Scroll down to "Partitions").

Quoting:

Blobs – Since the partition key is down to the blob name, we can load balance access to different blobs across as many servers in order to scale out access to them. This allows the containers to grow as large as you need them to (within the storage account space limit). The tradeoff is that we don’t provide the ability to do atomic transactions across multiple blobs.

Answer 2

Everyone has given you excellent answers around accessing blobs directly. However, if you need to list blobs in a container, you will likely see better performance with the many-container model. I just talked with a company who's been storing a massive number of blobs in a single container. They frequently list the objects in the container and then perform actions against a subset of those blobs. They're seeing a performance hit, as the time to retrieve a full listing has been growing.

This might not apply to your scenario, but it's something to consider...