Which consistency models are used when reading data from DynamoDB?

When reading data from DynamoDB, the two consistency models utilized are strongly consistent and eventually consistent.

Strongly consistent reads ensure that the data returned reflects all writes that received a successful response prior to the read operation. This means that when a strongly consistent read is performed, it always returns the most up-to-date data available. This is crucial for applications that require the latest information immediately after a write, such as those that rely on the most recent user input or transactional data.

On the other hand, eventually consistent reads may return data that may not reflect the latest write operations. This model is more performant and can be useful for applications that can tolerate some latency in data freshness, as it allows for lower read latency and higher throughput. Eventually consistent reads give a system time to synchronize across all replicas, ensuring that the data will converge to the latest state over time.

The correct choice reflects these two key consistency models used in DynamoDB, highlighting the trade-off between immediacy and performance.