271 karma · joined December 8, 2019
* 2 parts.
- Vertical scale: We use LMDB as a key-value store. This one uses the power of memory mapping. It made our search engine use mainly the disk and will do not need a machine that will have TB of RAM.
- Horizontal scale. We are working on sharding and replications (Raft). Development is progressing well, and the functionality should come out soon.
* Currently, it is not monitored at all. This feature is planned. https://github.com/meilisearch/MeiliSearch/issues/523
* We use a queue for updates. You can find here the complete guide https://docs.meilisearch.com/guides/advanced_guides/asynchro...
* As I said previously, we are working on HA with a raft consensus.
* We will add snapshots in no time (disk folder saved in s3). A little more time for backups (version agnostic, need indexing).
We are already working with Louis Vuitton on an application in production. The app is in production from 9 months, and there hasn't been a single problem.
- Currently, we only support single filters. The multiple filters option is coming soon. https://github.com/meilisearch/MeiliSearch/issues/425
- Custom ranking rules on the fly is something imaginable on our solution. We didn't do it yet because it complexifies the search query parameters. We are waiting for feedback like yours to implement this kind of feature.
- To return only the field you need, it's already possible during the search https://docs.meilisearch.com/guides/advanced_guides/search_p.... To restrict attributes to search in during the query. We had this feature on a previous version. But like the last answer, no one used it, and it complexifies the search query.