Time series tables

With DynamoDB, when you are creating a table you are going to specify the throughput. So from that DynamoDB will allocate resources to serve your requirements with low latency as best as it can. The core concept is that you should identify the core pattern of your tables that will be accessed via an application and based on that analysis you can restructure your application and tables.

Let's say, for example, you are designing a table to map the customers' search patterns on your application on the Web. So you can design your DynamoDB table with hash and range type primary keys with consumer ID as the hash attribute and date/time as the range attribute. So within this application your customer data will grow indefinitely with time; however, your application will show the uneven access pattern across items given in the table. In this pattern, it is possible that the latest item will be more frequently accessed and eventually the older items will be rarely accessed. So if...