LanceDB vs Qdrant
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It is an open-source Vector Search Engine and Vector Database written in Rust. It deploys as an API service providing search for the nearest high-dimensional vectors. With Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more. | It is an open-source database for vector search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings. |
Easy to use API;
Fast and accurate;
Advanced filtering;
Rich data types;
Cloud-native and horizontally scaleable;
Efficient & performant | Production-scale vector search with no servers to manage;
Store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more);
Native Python and Javascript/Typescript support;
Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure |
Statistics | |
GitHub Stars 26.9K | GitHub Stars 7.9K |
GitHub Forks 1.9K | GitHub Forks 635 |
Stacks 54 | Stacks 3 |
Followers 20 | Followers 4 |
Votes 0 | Votes 0 |
Integrations | |
What are some alternatives to Qdrant, LanceDB?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
Sphinx
It lets you either batch index and search data stored in an SQL database, NoSQL storage, or just files quickly and easily — or index and search data on the fly, working with it pretty much as with a database server.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
TensorFlow.js
Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API
MkDocs
It builds completely static HTML sites that you can host on GitHub pages, Amazon S3, or anywhere else you choose. There's a stack of good looking themes available. The built-in dev-server allows you to preview your documentation as you're writing it. It will even auto-reload and refresh your browser whenever you save your changes.
Polyaxon
An enterprise-grade open source platform for building, training, and monitoring large scale deep learning applications.
Streamlit
It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.
