gaul / are-we-consistent-yet

Compare eventual consistency of object stores
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aws-s3 azure consistency google-cloud-storage openstack-swift s3

Are We Consistent Yet?

Observed and documented eventual consistency of object stores, e.g., Amazon S3, OpenStack Swift.

What is eventual consistency?

Traditional systems provide strong consistency, where clients can immediately view updates. Some distributed systems relax their consistency model to allow greater availability or better performance. Eventual consistency manifests itself to clients as stale views of data.

Observed consistency

We ran a test in which we wrote (i.e., create, update, delete) an object and then attempted to read the object. Across many trials, we count the number of times the object was not immediately available. When the object is not immediately found, it's an occurrence of observed eventual consistency.

Observed instances of eventual consistency with a number of operations during tests around 17 December 2014 with a 1-byte object size:

Provider read after create read after delete read after overwrite list after create list after delete number of operations
Amazon S3 (us-standard) * * * 16 * 100,000
Amazon S3 (us-standard†) 16 8 12 8 3 1,000
Amazon S3 (us-west) - 1 1 * * 100,000
Ceph (DreamObjects) - - - - - 1,000
Google Cloud Storage - - - 2 2 1,000
Microsoft Azure Storage - - - - - 1,000
OpenStack Swift (Rackspace) - 17 3 30 20 1,000

Legend:

Documented consistency

References