Replication for MeiliSearch is on its way :) The main differentiator is that MeiliSearch algorithms are made for end-user search not for complex queries. MeiliSearch focus on site search or app search, not analytics on hyper large datasets
It's a dataset of 107M songs, 7.6 Gb of compressed files which represents 250 Gb of disk usage by MeiliSearch. We are indexing the release, song and artists names.
We also work with a dataset of 2M cities that we can index in less than 2 minutes when the db uses 3 shards.
We are working on both replication (for high availability and we may use the Raft consensus) and distribution (sharding to scale horizontally and keeping low latency)
