Support Sonic integration in addition to Elastic

Sonic is a fast, lightweight and schema-less search backend. It ingests search texts and identifier tuples that can then be queried against in a microsecond's time. It implemented in Rust too, which makes it a perfect complement to Vector.

Sonic can be used as a simple alternative to super-heavy and full-featured search backends such as Elasticsearch in some use-cases. It is capable of normalizing natural language search queries, auto-completing a search query and providing the most relevant results for a query. Sonic is an identifier index, rather than a document index; when queried, it returns IDs that can then be used to refer to the matched documents in an external database.

A strong attention to performance and code cleanliness has been given when designing Sonic. It aims at being crash-free, super-fast and puts minimum strain on server resources (our measurements have shown that Sonic - when under load - responds to search queries in the μs range, eats ~30MB RAM and has a low CPU footprint; see our benchmarks).

No files, tests, or entry points are named. Start by reviewing Vector’s existing Elasticsearch integration and the Sonic API documentation, then determine the required configuration, ingestion, and query behavior; done means Sonic can be used as an alternative search backend with coverage for the supported behavior.