Neural Search Frameworks: A Head-to-Head Comparison

11 min readDec 23, 2022

While working on this blog post I had a privilege of interacting with all neural search frameworks key developers / leadership: Malte Piestch (Haystack), Amin Ahmad (Vectara), Florian Hönicke (Jina AI), David Mezzetti (txtai), Daniel Vassilev (Relevance AI), George Sivulka and Swetha Revanur (Hebbia), Aarne Talman and myself (Muves). The blog title has been generated by ChatGPT. Hacker News thread: https://news.ycombinator.com/item?id=34107410

As the neural search journey develops further, we discover new frontiers of semantic, multimodal…

Neural Search Frameworks: A Head-to-Head Comparison

Written by Dmitry Kan

More from Dmitry Kan

Not All Vector Databases Are Made Equal

A detailed comparison of Milvus, Pinecone, Vespa, Weaviate, Vald, GSI and Qdrant

Speeding up BERT Search in Elasticsearch

Neural Search in Elasticsearch: from vanilla to KNN to hardware acceleration

How to Choose a Vector Database

Last week Thursday I spoke at Pinecone’s workshop by invitation of Greg Kogan, VP Marketing, Pinecone — one of the 7 vector databases…

Fun With Apache Lucene and BERT Embeddings

After publishing the blog post on neural search with BERT and Solr (6.6.0), I got a few questions on how to run this with version 8.6.x of…