Annoy Alternatives
Similar projects and alternatives to annoy
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OPS
OPS - Build and Run Open Source Unikernels. Quickly and easily build and deploy open source unikernels in tens of seconds. Deploy in any language to any cloud.
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Scout APM
Less time debugging, more time building. Scout APM allows you to find and fix performance issues with no hassle. Now with error monitoring and external services monitoring, Scout is a developer's best friend when it comes to application development.
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hora
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
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milvus
An open-source vector database for embedding similarity search and AI applications.
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ann-benchmarks
Benchmarks of approximate nearest neighbor libraries in Python
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bootcamp
Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc. (by milvus-io)
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horapy
🐍 Python bidding for the Hora Approximate Nearest Neighbor Search Algorithm library
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awesome-vector-search
Collections of vector search related libraries, service and research papers
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Reviews and mentions
- Faiss: Facebook's open source vector search library
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I built an Image Search Engine using OpenAI CLIP and Images from Wikimedia
I used for this project Flask and OpenAI CLIP. For the vector search I used approximate nearest neighbors provided by spotify/annoy. I used Flask-SQLAlchemy with GeoAlchemy2 to query GPS coordinates. The embedding was done using UMAP.
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Facebook AI Similarity Search (Faiss)
I’ve used annoy [0] for vector-similarity search before. Does anyone know the differences between Faiss and annoy? Thanks!
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txtai - Semantic search backed by machine-learning powered workflows
🔎 Large-scale similarity search with multiple index backends (Faiss, Annoy, Hnswlib)
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NLP Method(s) for Finding Commonalities?
Create a ANN search index using Annoy or FAISS
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Announcing Hora 0.1.0, an approximate nearest neighbor search algorithm library in rust
How does this compare to something like annoy, it's used and written by Spotify.
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[D] can you use a decision tree for clustering?
https://medium.com/@kevin_yang/simple-approximate-nearest-neighbors-in-python-with-annoy-and-lmdb-e8a701baf905
- Introduction to Locality-Sensitive Hashing
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How would you go about building a content based recommendation system with reinforcement?
Spotify develops Annoy for its internal recommender systems. Vector similarity search for clustering as well as ANN model tracing over the vector pool.
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Using the Spotify Algorithm to Find High Energy Physics Particles
Tracking particles in High Energy Physics is about connecting together the hits produced by the same particle. In a typical High Luminosity collision event, 100K hits are produced by 10K particles leading to an average particle size of 10 hits. The challenge is then to connect the right 10 hits together from a collection of similarly looking 100K hits and to do it under a second! This post is a python guide to particle tracking with Approximate Nearest Neighbor library Annoy.
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Vald: A Highly Scalable Distributed Vector Search Engine
With only 100k vectors, why didn’t you just use Annoy? It’s been around for many years and it is fast, reliable, super easy to use and handles pretty large data quite well too.
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[D] Hashing techniques to compare large datasets?
There is a technique called similarity hashing to find sets of similar items in a large database in O(1) time. (Indexing costs O(n)). Maybe you find the Annoy library useful: https://github.com/spotify/annoy
Stats
spotify/annoy is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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