DynamoDB

The migration itself is small: model a table around lookups (partition key on the prompt identifier), read the hot path by key, and synchronize by checksum rather than by timer or every deployment.

Provisioned Capacity requires setting read/write capacity units per second (RCU/WCU) and using Auto Scaling to adjust as load fluctuates.

DynamoDB does not provide versioning directly, but it can be modeled by adding a version number to the key (partition key as the prompt identifier, sort key as the version number, plus a current pointer item).

A conditional write uses ConditionExpression to verify at write time whether a certain attribute meets a specific condition; the write is performed only if the condition holds, otherwise it returns a failure, similar to optimistic locking.

This solution has been running stably in production.

DynamoDB read throughput scales with the table rather than a fixed service quota; on-demand capacity absorbs bursts, while provisioned capacity with auto scaling handles steady loads.

DynamoDB single-item reads by primary key (GetItem) keep latency steady at single-digit milliseconds.

On-Demand Capacity is a DynamoDB billing and capacity mode that requires no pre-specified read/write capacity units, scales automatically based on actual request volume, and bills by request count.

Instant messaging systems use Cassandra or DynamoDB for message storage to handle hundreds of thousands of writes per second, while user and group metadata is placed in PostgreSQL.

Typical distributed storage such as Amazon S3, DynamoDB, Cassandra, and a large number of SaaS service provider APIs are all built on the eventual consistency model.

When connecting an event source to compute that can produce the same kind of event, you must consider whether the output will become the input, otherwise a recursive loop may be triggered (such as an S3→Lambda loop, or a DynamoDB stream writing back to its own table).

A developer migrated the read side of prompts to DynamoDB, kept the hosted service as the single source of truth, and maintained data consistency through checksum write-through synchronization, completely eliminating the rate-limiting problem.