Are you asking how Dynamo compares at the storage level? Like in comparison to S3? As a key-value database it doesn’t even have a native aggregation capability. It’s a very poor choose for OLAP.
BigQuery is comparable to DuckDB. I’m curious how the various Redshift flavors (provisioned, serverless, spectrum) and Spark compare.
I don’t have a lot of experience with DuckDB but it seems like Spark is the most comparable.
BigQuery is built for the distributed case while DuckDB is single CPU and requires the workarounds described in the article to act like a distributed engine.
And yeah these days you can boost a single machine to enormous specifications. I guess the main difference will be the cost. A distributed engine can "lease" a little bit of time here and there, while a single RAM engine needs to keep all that capacity ready for when it is actually needed.
In theory a Zen 5 / Eypc Turin can have up to 4TB of ram. So how would a more traditional non-clustered DB stand up?
1000 k8s pods, each with 30gb of ram, there has to be a bit of overhead/wastage going on.