An Indexer that works out-of-the-box when you have less than 100K stored Documents
An Indexer that works out-of-the-box when you have less than 100K stored Documents. U100K means under 100K. At 100K stored Documents with 768-dim embeddings, you can expect 300ms for single query or 20~120QPS for batch queries. Results are full Documents.
U100KIndexer leverages jina.DocumenetArrayMemmap as the storage backend and .match() to conduct nearest neighbours search. It returns the full Documents as-is, hence no need to concatenate it with another key-value indexer to retrieve Documents.
Pros & cons
Pros
- Exhaustive search: highest recall
- Fast indexing
- Acceptable query performance under 100K
- Always return full Documents
- No extra dependencies
Cons
Performance
The indexing and query performance on 768-dim embeddings is as follows (unit is