Most distributed cloud services take one of two approaches to ensuring data consistency:
One approach, strong consistency, doesn't allow reads until all associated writes are complete. Any read always returns the latest version of an item. If you use strong consistency for your data, your application is only as fast as the latency among all the regions where you store data.
The other approach, eventual consistency, is a lazier approach to working with data. It's more focused on applications that need to read data as soon as it's written. Data is read at any time, but there's a risk that it could be changed by another write. That leaves you with a level of indeterminacy in your data: You know at some point it's going to be accurate, just not when that will be. Data may arrive in any order, so don't use eventual consistency for series data. There's even the chance that if you read the same item twice, the second time could return older data than the first.
Posted By Blogger to HDGEM at 5/30/2017 04:30:00 PM