Looking for something like currentslab/awesome-vector-search? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 21 are open source.
Curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search.
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | LLM App | — | Yes | — |
| 2 | distilabel | — | Yes | — |
| 3 | Zilliz Cloud | — | Not stated | Web |
| 4 | VectorChord | — | Not stated | — |
| 5 | Awesome Production Machine Learning | — | Yes | — |
| 6 | txtai | — | Yes | Web |
| 7 | Awesome Tensor Compilers | — | Not stated | — |
| 8 | GPTCache | — | Yes | — |
| 9 | Sonnet | — | Yes | — |
| 10 | Deepchecks | — | Yes | — |
Pathway offers cloud templates for RAG, AI pipelines, and enterprise search that stay synchronized with connected data sources.
Synthetic data and AI feedback pipelines can be built with Distilabel, a framework based on research papers.
Zilliz Cloud provides a managed vector data platform powered by Milvus, with real-time search and data operations across major cloud regions.
Scalable, fast, and disk-friendly vector search in Postgres, the successor of pgvecto.rs.
Curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning.
txtai combines semantic search, language-model orchestration and AI workflows in an open-source framework.
List of awesome compiler projects and papers for tensor computation and deep learning.
GPTCache provides semantic caching for large language models and integrates with LangChain and LlamaIndex.
Build neural networks and support machine learning research with Sonnet, a library based on TensorFlow.
Deepchecks tests and validates machine learning models and data, covering workflows from research through production.
Xinference runs language, speech, and multimodal models through a unified inference API across cloud, on premises, or laptop setups.
dstack coordinates AI compute and supports training and inference across GPU clouds, Kubernetes, VMs, and bare metal.
N2D2 provides an open source CAD framework for deep neural network simulation and application building.
Catniff provides JavaScript developers with a Torch-like deep learning framework.
The ChefBoost Python framework supports decision trees such as ID3, C4.5, CART, CHAID, regression trees, and ensemble methods.
The Datumbox framework is written in Java for developing machine learning and statistical applications.
DJL is a Java framework for running deep learning models across different engines.
The linfa project provides a machine learning framework written in Rust.
PyToune provides a simplified framework and utilities for working with PyTorch.
PaddlePaddle provides a deep learning framework for training models across devices and platforms.
Hypernets offers a general automated machine learning framework for developing end to end AutoML toolkits in specific domains.
FATE supports federated learning through an industrial grade framework.
A JavaScript Native PyTorch-aligned Machine Learning Framework, built from scratch on WebGPU.
MLX provides an array computing framework designed for Apple silicon devices.
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
