Hmm, as a former AWS employee who has used both heavily, my experience has been the opposite.

Terraform’s AWS provider calls the APIs directly, whereas CDK generates Cloudformation, an abstraction on top of the AWS APIs. For me, using Terraform was significantly faster than applying the same stack via CDK.

Or do you mean you’re able to iterate faster writing CDK vs TF?

Thinking back on it, we always used Terraform with Pulumi, which creates its own abstraction layer for a CF stack. It's hard to pinpoint where the root cause of the slowness was.. but in principle having fewer abstractions allowed us to iterate faster, and fix the bugs more quickly.

From my experience, terraform is almost always slow because it's making API calls out to the cloud providers, and a lot of that in turn is slow because many providers offer "eventually consistent" which terraform needs to compensate for by doing roundtrips to validate that changes are have become visible (applys failing because of that was a common problem in the early days of terraform).

I'd rather devote my time learning an agnostic tool like terraform. I can be part of your team right now working on AWS but tomorrow I might be working for an Azure shop.

CDK synth is reasonably fast but CF is really slow

What does the AWA CDK do differently than use public APIs?

CDK generates cloudformation stacks. Those stacks are deployed as units, within AWS itself. AWS treats all the resources as part of that stack etc; it's a concept entirely proper to AWS.

Terraform can create cloudformation stacks as well, you just have to write the resources for it. It doesn't really make sense to do that. I also don't know that it's … "faster" in any way; cfn is really slow.

It’s just tags on the resources and a managed statefile. There isn’t anything different between a bucket created via CDK and a bucket created via terraform, the resources are the same and the API calls to create them are also the same.