If you really need search, I think its the clear winner still. I don't think its terribly hard to manage/operate, just that you do need to do some initial planning otherwise it will balloon out of control.

Dynamic mappings can mess things up really easily, so its best to disable them in favor of using a pre-defined static map for the type of documents you will be ingesting. What I've encountered in the past that usually causes things to break, is when 90% of your documents contain a field called "Date" that contains a ANSI date field, but the other 10% contain "Null" (string instead of an ANSI date). Since the documents don't match the dynamically generated mapping, they fail to be indexed.

Shard management is also critical and this largely depends on the type of data you are indexing. If the data in ES is unique (not just a copy of a database you already have), you will want to have some sort of cross-region/DC replication strategy as well as a backup strategy.

Fortunately both of these are pretty easy. ES has a mechanism of using tags that allows you to define things like regions, data centers, really whatever you want, and shards can be routed based on rules defined over these tags.

A setup I've used in the past is to have 5 nodes in LAX DC 5 nodes in LAS DC, any data that is ingested into LAX is replicated into shards in LAS and vice versa.

Backup to S3 is rather trivial now thanks to the built in export options in the newer versions of ES.

With a little bit of planning ES can be a great addition to your stack, just be sure you do the initial engineering so you can avoid a big headache in the future.