Our API response times have doubled since implementing semantic search using vector databases, what troubleshooting steps should I run right now?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Our API response times have doubled since implementing semantic search using vector databases, what troubleshooting steps should I run right now?
1 real search · 1 real-search pass
vector database performance troubleshooting latency HNSW indexing query latency official documentationGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
vector database performance troubleshooting latency HNSW indexing query latency official documentation Google ↗
- Best Practices for Atlas Vector Search Performance with MongoDB Course · learn.mongodb.com
- HNSW · doris.apache.org