Where embeddings live, how they're indexed, and how similarity search behaves at scale.
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13 articles
Listed inPerforming Similarity SearchVector Databaseson
Cosine and dot product rank the same on normalized vectors. The decision that actually changes your results is where the filter runs.
Listed inSupabase VectorVector Databaseson
Vectors as a column, so the filter is a WHERE clause on columns you already have and a row and its embedding land in one transaction.
Listed inIndexing EmbeddingsVector Databaseson
Qdrant's explainer on HNSW, payload indexes, and the quantization trade-offs behind recall and memory.
Listed inPurpose and FunctionalityVector Databaseson
A B-tree cannot find nearest neighbors, exact search stops scaling, and approximate search trades a guarantee for speed. Sometimes you need none of it.
Listed inLanceDBVector Databaseson
An embedded retrieval library rather than a server, with multimodal assets beside the vectors. Plus what the project does not actually claim.
Listed inWeaviateVector Databaseson
A search service rather than a vector column or an embedded library. Hybrid search fuses keyword and vector ranking, which recovers the exact identifiers embeddings lose, and the index types include a flat one suited to many small per-tenant datasets.
Listed inChromaVector Databaseson
The persistent client gets a working query with no infrastructure decision, and the collection code survives the move to a server. Concurrency, the directory's lifetime and backups are the bill that arrives with traffic.
Listed inMongoDB Atlas Vector SearchVector Databaseson
Vector indexes inside documents you already store.
Listed inIndexing EmbeddingsVector Databaseson
HNSW, IVF, and the recall/latency/memory triangle you're choosing a point on.
Listed inQdrantVector Databaseson
Rust-based vector search with rich payload filtering and quantization.
Listed inVector DatabasesVector Databaseson
Purpose-built stores for nearest-neighbour search over millions of vectors.
Listed inFAISSVector Databaseson
Meta's ANN library — a fast index, not a database.
Listed inPineconeVector Databaseson
Fully managed, serverless vector search with namespaces and metadata filters.