I've found DDB to be exceptional for use cases where eventual consistency is OK and you have a few well defined query patterns. This is a large number of use cases so it's not too limiting. As the number of query patterns grow, indices grow, and costs grow (or pray for your soul you attempt to use DDB transactions to write multiple keys to support differing query patterns). If you need strong consistency, your cost and latency also increases.
Oh, and I'd avoid DAX. Write your own cache layer. The query cache vs. item cache separation[1] in DAX is a giant footgun. It's also very under supported. There still isn't a DAX client for AWS SDK v2 in Go for example[2].
Oh, and I'd avoid DAX. Write your own cache layer. The query cache vs. item cache separation[1] in DAX is a giant footgun. It's also very under supported. There still isn't a DAX client for AWS SDK v2 in Go for example[2].
1 - https://docs.aws.amazon.com/amazondynamodb/latest/developerg...
2 - https://github.com/aws/aws-dax-go/issues/2