"A table is a collection of items, and an item is a collection of namedattributes. Items are uniquely identified by apartition key attribute and an optionalsort key attribute. The partition key determines where (i.e. on what computer) an item is stored. The sort key is used to get ordered ranges of items from a specific partition. That's is, that's the whole data model. Sure, there's indexes and transactions and other features, but at its core, this is it. Put another way:"
"A DynamoDB table is - partition keys are hash table keys, and sort keys are B-tree keys. Because of this, any access not based on partition and sort key is expensive, since you end up doing a full table scan. If you were to implement this model in Python, it'd look something like this: Philosophy One can't help but feel this kind of simplicity would be severely limiting."
Amazon DynamoDB is a managed NoSQL database supporting key-value and document data structures for scalable, high-performance applications. Tables contain items made of named attributes, uniquely identified by a partition key and an optional sort key. The partition key determines storage placement while the sort key enables ordered ranges within a partition. Conceptually, partition keys act as hash-table keys and sort keys as B-tree keys, so accesses that do not use those keys require full table scans and are expensive. DynamoDB's low-level simplicity shifts query planning and some index management responsibilities to the application, increasing developer responsibility for access patterns.
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