biggraph-wikidata-searc VS awesome-vector-search

Compare biggraph-wikidata-searc vs awesome-vector-search and see what are their differences.

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biggraph-wikidata-searc awesome-vector-search
1 20
- 1,275
- 2.5%
- 6.1
- 21 days ago
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

biggraph-wikidata-searc

Posts with mentions or reviews of biggraph-wikidata-searc. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-14.

awesome-vector-search

Posts with mentions or reviews of awesome-vector-search. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-07.

What are some alternatives?

When comparing biggraph-wikidata-searc and awesome-vector-search you can also consider the following projects:

biggraph-wikidata-search-with-weaviate - Search through Facebook Research's PyTorch BigGraph Wikidata-dataset with the Weaviate vector search engine

pgvector - Open-source vector similarity search for Postgres

hnswlib - Header-only C++/python library for fast approximate nearest neighbors

annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

google-research - Google Research

qdrant - Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

sample-apps - Repository of sample applications for https://vespa.ai, the open big data serving engine

Milvus - A cloud-native vector database, storage for next generation AI applications

semantic-search-through-wikipedia-with-weaviate - Semantic search through a vectorized Wikipedia (SentenceBERT) with the Weaviate vector search engine

featureform - The Virtual Feature Store. Turn your existing data infrastructure into a feature store.

vearch - Distributed vector search for AI-native applications