Open Source C++ Vector Search Engines

Gamma is the core vector search engine of Vearch. It is a high-performance, concurrent vector search engine, and supports real-time indexing vectors and scalars without lock. Differently from the general vector search engine, Gamma can store and index a document containing scalars and vectors, providing the ability to quickly index and provides the ability of quickly indexing and filter by numeric scalar fields. The work of design and implementation of real-time indexing has been published in our Middleware paper. As for the part of similarity search of vectors in Gamma, it is mainly implemented based on faiss which is an open-source library developed by Facebook AI Research. Besides faiss, it can easily support other approximate nearest neighbor search(ANN) algorithms or libraries.

Make AI-driven decisions using your data, in real-time. At any scale, with unbeatable performance. Vespa is a full-featured text search engine and supports both regular text search and fast approximate vector search (ANN). This makes it easy to create high-performing search applications at any scale, whether you want to use traditional techniques or a modern vector-based approach. You can even combine both approaches efficiently in the same query, something no other engine can do. Recommendation, personalization and targeting involves evaluating recommender models over content items to select the best ones. Vespa lets you build applications which does this online, typically combining fast vector search and filtering with evaluation of machine-learned models over the items. This makes it possible to make recommendations specifically for each user or situation, using completely up to date information.