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qdrant
Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Solid work OpenAI, though I'd definitely like to see some more benchmarks on a wider variety of datasets in addition to the ones listed in the post. Regardless, it's good to see embeddings becoming more and more mainstream and easier to leverage out-of-box. We tried image embeddings many moons ago (2015) with AlexNet trained across a custom dataset, but we still had to add quite a few custom roles post-inference.
A large selling point for ada-002 embeddings seems to be the reduced dimensionality. While lower-dimensional embeddings definitely help performance, I would say it's still highly dependent on the index that's being used. Graph- and tree-based indexes will benefit less than ones based on IVF (https://zilliz.com/blog/vector-index), as they do fewer overall distance computations during query time, but the speedup would still be significant.
Still been meaning to try semantic search across Wikipedia via text embeddings. Will definitely play around with OpenAI + Milvus (https://github.com/milvus-io/milvus).
ES and OS are desperately slow because based on the lucene vector search index. A dedicated vector database like Qdrant will be always a better choice https://github.com/qdrant/qdrant
Do we have any idea why lucene vector search underperforms? As of lucene 9.1 (and elastic 8.4), it runs the same sort of filtered/categorical HNSW that qdrant runs (https://lucene.apache.org/core/9_1_0/core/org/apache/lucene/...). Qdrant's benchmarking code (https://github.com/qdrant/vector-db-benchmark/blob/9263ba/en...) does use the new filtered ann query with elastic 8.4, so it appears to be a fair benchmark. Why is lucene/elastic so much slower? Is it a rust vs. java thing? Or some memory management issues?