Redis As A Vector Database: Billion-Scale Fast Vector Similarity Search with RediSearch
In this exciting video, we explore the power of Redis, a versatile key-value store, and its remarkable RediSearch module. We dive into the world of high-dimensional data and witness the incredible speed and accuracy of the Hierarchical Navigable Small World (HNSW) algorithm, enabling us to perform approximate nearest neighbor searches in the blink of an eye. Redis takes center stage as a vector database, efficiently storing and retrieving vast amounts of vector data. We embark on a journey to uncover the magic behind Redis’ lightning-fast search capabilities, enabling us to locate the nearest neighbors of a given query vector among billions of others in just milliseconds.
But that’s not all! Our exploration wouldn’t be complete without the assistance of the deepface library for Python. We witness the transformation of facial images into vector embeddings, opening up a whole new realm of possibilities for face recognition and analysis. Join us on this captivating adventure as we unravel the mysteries of Redis, RediSearch, HNSW, and deepface, showcasing their incredible synergy and pushing the boundaries of speed and efficiency in vector-based search and analysis. Get ready to be amazed by the power of technology and its limitless potential in the world of data exploration.
Tutorial: https://sefiks.com/2023/07/13/redis-as-a-vector-database-fast-vector-similarity-search-with-redisearch/
If you like this video, you may like these too:
– Fast Vector Similarity Search with Facebook Faiss: https://youtu.be/6AmEvDTKT-k
– Fast Vector Similarity Search with Spotify Annoy: https://youtu.be/Jpxm914o2xk
– Fast Vector Similarity Search with ElasticSearch: https://youtu.be/i4GvuOmzKzo
– Fast Vector Similarity Search with NMSLIB: https://youtu.be/EVBhO8rbKbg
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