{"repo":"Semafind/semadb","free":true,"listed":false,"github":"https://github.com/Semafind/semadb","clone":"git clone https://github.com/Semafind/semadb.git","description":"No fuss multi-index hybrid vector database / search engine","language":"Go","stars":32,"topics":["search-engine","vector-database"],"license":"Apache-2.0","category":"databases-storage","readme_excerpt":"No fuss multi-index hybrid vector database / search engine SemaDB is a multi-index, multi-vector, document-based vector database / search engine. It is designed to offer a clear and easy-to-use JSON RESTful API. The original components of SemaDB were built for a knowledge-management project at Semafind before it was developed into a standalone project. The goal is to provide a simple, modern, and efficient search engine that can be used in a variety of applications. Looking for a hosted solution? SemaDB Cloud Beta is available on RapidAPI. Features ⚡ - Vector search : leverage the power of vector search to find similar items and build AI applications. SemaDB uses the graph-based Vamana algorithm to perform efficient approximate nearest neighbour search. - Keyword / text search : search for documents based on keywords or phrases, categories, tags etc. - Geo indices : search for documents based on their location either via latitude and longitude or geo hashes. - Multi-vector search : search across multiple vectors at the same time for a single document each with own index. - Quantized vector search : use quantizers to change internal vector representations to reduce memory usage. - Hybrid search : combine vector and keyword search to find the most relevant documents in a single search request. Use weights to adjust the importance of each search type. - Filter search : filter search results based on other queries or metadata. - Hybrid, filter, multi-vector, multi-index search : ","default_branch":null,"files":null,"tree":[],"storefront":"/r/Semafind","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/Semafind/semadb/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}