AmableDB is a fast nosql database to find similar float-vectors in big datasets. For that purpose, it depends on the NMSLIB library. All CRUD-Operations are supported via easy HTTP-Requests (GET AND POST) so all programming language can use this project. Just pull the Docker-Image and start quering. You can find a documentation in the Wiki.
For my project Hive Discover I had to do some KNN-Search over Post-Data. A neural network analyzed the text-body of different posts. As a result, I got 46 different values from 0 - 1 which represents the 46 categories. So to find similar posts I had to find similar vectors and I looked for a library for this kind of job. I ended up using the NMSLIB-Implementation of k-Nearest-Neighbor. I found out that elastic-search supports search operations but it required way to much memory. So I thought: Can this not be lightweight? Also elastic-search does not support directly the knn-Search.
That is why I created the amableDB project. It should help people who want to find quick and easy similar vectors with different search algorithms (currently only the knn-Search is available; later will be more). Also machine learning algorithms like SVC or Linear Regression are planned which should be easy to perform on collections.
Simply run these two commands and you got your first node running:
[1] docker pull christopher2002/amable-db:latest[2] docker run -d --name amabledb -p 3399:3399 christopher2002/amable-db:latest
For more information visit the Docs