Info
ANN-Benchmarks is a benchmarking environment for approximate nearest neighbor algorithms search. This website contains the current benchmarking results. Please visit http://github.com/erikbern/ann-benchmarks/ to get an overview over evaluated data sets and algorithms. Make a pull request on Github to add your own code or improvements to the benchmarking system.
Benchmarking Results
Results are split by distance measure and dataset. In the bottom, you can find an overview of an algorithm's performance on all datasets. Each dataset is annoted by (k = ...), the number of nearest neighbors an algorithm was supposed to return. The plot shown depicts Recall (the fraction of true nearest neighbors found, on average over all queries) against Queries per second. Clicking on a plot reveils detailled interactive plots, including approximate recall, index size, and build time.
Benchmarks for Single Queries
Results by Dataset
Distance: Angular
glove-100-angular (k = 10)
glove-25-angular (k = 10)
nytimes-256-angular (k = 10)
Distance: Euclidean
fashion-mnist-784-euclidean (k = 10)
gist-960-euclidean (k = 10)
sift-128-euclidean (k = 10)
Distance: Hamming
sift-256-hamming (k = 10)
word2bits-800-hamming (k = 10)
Distance: Jaccard
kosarak-jaccard (k = 10)
Results by Algorithm
- Algorithms:
- faiss-ivf
- scann
- pgvector
- annoy
- glass
- hnswlib
- BallTree(nmslib)
- vald(NGT-anng)
- hnsw(faiss)
- NGT-qg
- qdrant
- n2
- Milvus(Knowhere)
- qsgngt
- faiss-ivfpqfs
- mrpt
- redisearch
- SW-graph(nmslib)
- NGT-panng
- pynndescent
- vearch
- hnsw(vespa)
- vamana(diskann)
- flann
- luceneknn
- weaviate
- puffinn
- hnsw(nmslib)
- bruteforce-blas
- tinyknn
- NGT-onng
- elastiknn-l2lsh
- sptag
- ckdtree
- kd
- opensearchknn
- datasketch
- bf
faiss-ivf
scann
pgvector
annoy
glass
hnswlib
BallTree(nmslib)
.png)
vald(NGT-anng)
.png)
hnsw(faiss)
.png)
NGT-qg
qdrant
n2
Milvus(Knowhere)
.png)
qsgngt
faiss-ivfpqfs
mrpt
redisearch
SW-graph(nmslib)
.png)
NGT-panng
pynndescent
vearch
hnsw(vespa)
.png)
vamana(diskann)
.png)
flann
luceneknn
weaviate
puffinn
hnsw(nmslib)
.png)
bruteforce-blas
tinyknn
NGT-onng
elastiknn-l2lsh
sptag
ckdtree
kd
opensearchknn
datasketch
bf
Contact
ANN-Benchmarks has been developed by Martin Aumueller ([email protected]), Erik Bernhardsson ([email protected]), and Alec Faitfull ([email protected]). Please use Github to submit your implementation or improvements.
