[mey]

So how would that compare to DynamoDB or BigQuery? (I have zero interest in paying for running that experiment).

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.

[mulmen]

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.

[fifilura]

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.

[tishj]

DuckDB is not single CPU, it's single machine - big difference

[fifilura]

Fair enough i slipped. And single RAM.

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.

[mulmen]

Ah ok. Maybe that does make sense as a comparison to ask if you need an analytics stack or can just grind through your prod Dynamo.