{"repo":"prrao87/lancedb-study","free":true,"listed":false,"github":"https://github.com/prrao87/lancedb-study","clone":"git clone https://github.com/prrao87/lancedb-study.git","description":"Comparing LanceDB and Elasticsearch for full-text search and vector search performance","language":"Python","stars":30,"topics":["lance","lancedb","vector-database","vector-db","embedded-database"],"license":"MIT","category":"databases-storage","readme_excerpt":"LanceDB vs Elasticsearch benchmark Reproducible benchmark project comparing full-text search (FTS) and vector search between LanceDB and Elasticsearch on the Wine Reviews dataset. Setup Run from repo root: Create env files: - LanceDB defaults work out of the box if you keep lancedb/.env.example values. - Elasticsearch requires a valid DB password set up in elasticsearch/.env for your local container setup. Shared benchmark queries A set of keyword-based queries (for full-text search) and vector search queries are present in the following two files. These are sampled at random, 1000 times (with repetition) to create the query suites for the benchmarks. - bench queries/keyword terms.txt - bench queries/vector terms.txt Benchmark protocol The benchmark is run in two modes: a) using the async Python clients directly in LanceDB and Elasticsearch, and b) via a FastAPI REST server that calls the respective query endpoint for LanceDB and Elasticsearch. Both modes use the same run protocol, averaged over 3 runs, per the following criteria: - Fixed query count: 1000 queries per search type ( fts , vector ) per trial - Fixed trial count: 3 trials per search type - Results containing QPS, P50/P95/P99 latencies Embedding model The nomic-ai/modernbert-embed-base embedding model on Hugging Face, with 256 dimensions, is used for generating embeddings on the text fields. LanceDB workflow Run the following steps to ingest the data with embeddings, create and index and run the benchmarks for La","default_branch":null,"files":null,"tree":[],"storefront":"/r/prrao87","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/prrao87/lancedb-study/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}