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spring-ai/vector-stores/output/11-ops-footprint.txt
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asmhatre 74e6334704 Add vector-stores module: one dataset through VectorStore on pgvector, Redis, Qdrant and Elasticsearch
Ingest time, recall@10 against exact search, latency, metadata filtering and running cost, with
the defaults that cost recall reproduced and every figure written to output/.
2026-10-09 05:50:01 +00:00

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30000 x 384 float32 = 46 MB of raw vectors. PSS = proportional set size of the service's processes, read from /proc, after loading and querying.
store PSS MB size of the loaded data, as the store reports it
pgvector 150 table+toast 59 MB, hnsw index 59 MB
redis 422 used_memory 434 MB for 30000 keys (everything lives in RAM); one document = 10600 bytes; vector_index_sz_mb=55.4
qdrant 173 storage dir 144 MB
elasticsearch 1544 index store.size/docs.count [{"store.size":"54.3mb","docs.count":"30000"}] (JVM heap fixed at -Xmx1g)