AquilaDB-Python

Python client library for AquilaDB

install

pip install aquiladb

usage

# import AquilaDB client
from aquiladb import AquilaClient as acl

# create DB instance
db = acl('localhost', 50051)

# convert a sample document
# convertDocument
sample = db.convertDocument([0.1,0.2,0.3,0.4], {"hello": "world"})

# add document to AquilaDB
db.addDocuments([sample])

# create a k-NN search vector
vector = db.convertMatrix([0.1,0.2,0.3,0.4])

# perform k-NN from AquilaDB
k = 10
result = db.getNearest(vector, k)

AquilaDB

AquilaDB is a Resillient, Replicated, Decentralized, Host neutral storage for Feature Vectors along with Document Metadata. Do k-NN retrieval from anywhere, even from the darkest rifts of Aquila (in progress). It is easy to setup and scales as the universe expands.

Github: https://github.com/a-mma/AquilaDB

Docker Hub: https://hub.docker.com/r/ammaorg/aquiladb

Documentation (dedicated Wiki page): https://github.com/a-mma/AquilaDB/wiki

Resillient

Make sure your data is always available anywhere through any network. It is not necessory to be always online. Work offline, sync later.

Replicated

Your data is replicated over nodes to attain eventual consistency.

Decentralized

There is no single point of failure.

Host Neutral

Want to use AWS, Azure, G-cloud or whatever? Got a legion of laptops? Connect them together? No worries as long as they can talk each other.

Who is this for

• If you are working on a data science project and need to store a hell lot of data and retrieve similar data based on some feature vector, this will be a useful tool to you, with extra benefits a real world web application needs.
• Are you dealing with a lot of images and related metadata? Want to find the similar ones? You are at the right place.
• If you are looking for a document database, this is not the right place for you.

Technology

AquilaDB is not built from scratch. Thanks to OSS community, it is based on a couple of cool open source projects out there. We took a couch and added some wheels and jetpacks to make it a super cool butt rest for Data Science Engineers. While CouchDB provides us network and scalability benefits, FAISS provides superfast similarity search. Along with our peer management service, AquilaDB provides a unique solution.

created with ❤️ a-mma.indic (a_മ്മ)