Map/reduce views ("secondary indexes") are currently built by serializing JSON down a pipe to an external process called couchjs that links against a seven year old version of Mozilla Spidermonkey (1.8.5, released on March 31st 2011, and the only version it currently works with). This external process then pipes the map results back, again as JSON. Forget zerocopy; we're serializing and deserializing twice per document. Almost all of this "external view server" (the only kind AFAICT) is actually written in Javascript on that seven year old engine. Nothing is streaming; your map function is sandbox-evaled in that process, the results of a single call are stuffed into a Javascript array via .push, then stringified and printed on standard output as a single line. The entire internal "view server" protocol is based on a pipe of single-line JSON commands and data payloads. Performance (and likely security, due to age of the engine) in this subsystem is extremely poor IME.
You can write map/reduce views in Erlang itself as an alternative, but that engine is disabled by default due to security concerns – it's "not sandboxed". Performance in this area also appeared to be proportional to the code size of the map function, which sounded a lot like it was being serialized down a pipe with no caching.
If you make a change to a single view in a design document, the database system will rebuild all indexes in that design document unconditionally, even if the other view code hasn't changed. The only way to prevent this is to store a single view per design document, and manage those documents yourself.
Once you've endured your multi-day index rebuild on a couple million documents, you'll also have to issue an extra "cleanup" command to delete the old (now essentially useless) indexes. It's a full rebuild, so you need 2x the space at a minimum to pull it off.
The data itself is stored in a single file per shard, opened in O_APPEND mode, effectively serializing all writes on the shard. You also will not see kswapd active, ever, because the OS VMM is not being used effectively – no shared memory for IPC, and no use of mmap AFAICT.
Server-side changes feed filters appear to be extremely slow when compared to just filtering the results in the client.
Authorization: limiting read access will be difficult at best. Transactional behavior: no, aside from a single bulk write feature (make sure to use "all or nothing" mode though).
Logging: signal to noise ratio is poor. Giant stack traces for minor events. You may even see strings emitted as UTF-32 arrays of integers in base 10. Hope you brought an ASCII table at least.
Documentation: The following passage from section 5.2.5 of the CouchDB v2.1.1 manual just about says it all: "Views with the JavaScript query server are extremely slow to generate when there are a non-trivial number of documents to process. The generation process won’t even saturate a single CPU let alone your I/O. The cause is the latency involved in the CouchDB server and separate couchjs query server, dramatically indicating how important it is to take latency out of your implementation." I can't say anything nice here about that last sentence, so I'm just going to keep my mouth shut.
But worst of all: every time it starts up, it tells me "it's time to relax". Nothing about this is relaxing.
(These are my own private individually-held views, and do not reflect the views of any employer or organization)