AWS News Blog
Amazon SimpleDB Consistency Enhancements
We’ve added two new features to Amazon SimpleDB to make it even easier for you to implement several different data storage and retrieval scenarios.
The first new feature allows you to do a consistent read. Up until now, SimpleDB implemented eventually consistent reads. You now have the option to choose the type of read which best meets the needs of each part of your application. Before I dive into the specifics, here’s a quick guide to the two types of reads:
- Eventually consistent reads offer the lowest read latency and the highest read throughput. However, the reads can return data that has been made obsolete or overwritten by a very recent write. In general, the time window where this can occur is smaller than one second.
- Consistent reads always return the most recent data, with the potential for slightly higher read latency and a small reduction in read throughput.
SimpleDB’s Select and GetAttributes functions now accept an optional ConsistentRead flag. This flag has a default value of false, so existing applications will continue to use eventually consistent reads. If the flag is set to true, SimpleDB will return a consistent read.
The second new feature allows you to issue SimpleDB PutAttributes and DeleteAttributes operations on a conditional basis. In other words, you can tell SimpleDB to perform the indicated operation if and only if a given single-valued attribute has the value specified in the PutAttributes or Delete call. You can easily implement counters (the value itself is effectively the version number), delete accounts only if the current balance is zero, and insert an item only if it does not exist.
You can combine consistent reads and conditional operations to implement a form of optimistic concurrency control, or OCC. Let’s say that your form-based web application allows users to update their accounts and that you built it with SimpleDB. If you store a version number with each SimpleDB item, you can keep the data consistent even if several users or applications attempt to edit the same record at the same time. You would retrieve the data for display using an eventually consistent read, and then display the form so that the user can edit it. You would also read the associated version number from SimpleDB and associate it with the form or the editing session. When the user modifies and then attempts to save the data, you would use a conditional PutAttributes call to make sure that the data hadn’t been changed. If the update fails, you’d need to invoke some application-specific action to resolve the conflict before proceeding. OCC often obviates the need for long-term availability-impacting locks, transactions, timeouts, and other complex and sometimes messy programming constructs.
You can read more about consistency models in Werner’s newest blog post (he may be in mid-flight as I write this, but I am confident that his post will show up soon).