Huh. I've had the opposite experience. Neo4j has a pretty nice interface and package overall, but I was not impressed with the performance, and the developer experience was about on-par with Elasticsearch (not comparing the two databases, just the developer resources and communities). For general purpose use I've still not found anything better than Postgres (and yes, knowledge graphs I would consider general purpose). For my day-to-day work I'm constantly querying a regularly-updated knowledge graph consisting of >10M active, highly-connected nodes - I keep previous versions in the same database so I can traverse backwards through time. This is all on my laptop. No problems with latency or performance.
I'm always curious what people's use cases are with graph databases; do people find Cypher and SPARQL helpful? I've tried several times, but SQL is just so expressive. Postgres is still my favorite graph database (and CRUD RDBMS, and filesystem, and "data conversion tool").