HelixDB

Multi-model database for the AI era — document, graph, vector, and relational in one

SurrealDB is a multi-model database that natively combines document, graph, relational, key-value, and vector storage in a single engine. It eliminates the need for separate databases by handling structured queries, graph traversals, full-text search, and vector similarity in one SQL-like query language called SurrealQL. Built in Rust for performance and safety, it supports real-time subscriptions, row-level permissions, and embedded or distributed deployment modes.

High-performance vector database written in Rust for similarity search at scale.

Qdrant is a high-performance vector similarity search engine and database written in Rust. Designed for production-grade AI applications with advanced filtering, payload indexing, and distributed deployment. Supports billion-scale vector collections with sub-second query times. Popular choice for RAG, recommendation systems, and anomaly detection.

AI data runtime for multimodal datasets and vector search

Deep Lake is an open-source AI data runtime from Activeloop for storing, versioning, and querying multimodal data and embeddings. It fits teams building RAG, training, evaluation, or dataset-heavy agent workflows that need a bridge between vector search, structured metadata, and large image, text, audio, or video collections.

Embedding-first search and discovery engine for AI-powered product experiences.

Marqo is an open-source tensor search engine that combines embedding generation and vector search in a single API, removing the need to manage separate embedding pipelines and vector databases. Built for product discovery and multi-modal search, it lets teams index text, images, and structured data together, returning ranked results based on semantic similarity rather than keyword overlap.

AI-native state store with hybrid vector and full-text search

SeekDB is an open-source AI-native state store from the OceanBase ecosystem that combines MySQL-compatible data access with hybrid vector and full-text retrieval. It targets agent and AI application teams that need embedded or server deployment, copy-on-write style sandboxes, and searchable state without gluing together several separate storage layers.

Distributed AI compute engine for scaling Python and ML workloads

Ray is an open-source distributed computing framework built for scaling AI and Python applications from a laptop to thousands of GPUs. It provides libraries for distributed training, hyperparameter tuning, model serving, reinforcement learning, and data processing under a single unified API. Ray's public site highlights OpenAI and other enterprise users. Maintained by Anyscale with Apache-2.0 open-source licensing.

Unified framework for fine-tuning 100+ large language models

LLaMA-Factory is an open-source toolkit providing a unified interface for fine-tuning over 100 LLMs and vision-language models. It supports SFT, RLHF with PPO and DPO, LoRA and QLoRA for memory-efficient training, and continuous pre-training. The LLaMA Board web UI enables no-code configuration, while CLI and YAML workflows serve advanced users. Integrates with Hugging Face, ModelScope, vLLM, and SGLang for model deployment.

Ultra-fast SIMD-accelerated embedded vector database with TurboQuant compression

High-performance Rust and Python vector search index utilizing TurboQuant 2-to-4-bit data-oblivious quantization for ultra-compact memory footprint and zero-training ANN retrieval.

Serverless Postgres

Serverless Postgres platform separating storage and compute for branching, autoscaling, read replicas, instant restore, and scale-to-zero workloads. Neon works with standard PostgreSQL clients and ORMs, supports extensions such as pgvector, and sits inside a broader Neon backend platform with Auth, Data API, Functions, Object Storage, and AI Gateway features.

Microsoft's distributed approximate nearest neighbor search library and billion-scale vector engine

Microsoft's distributed approximate nearest neighbor search library and online vector serving engine, utilizing space-partition trees and relative neighborhood graphs for billion-scale semantic retrieval.

The open-source Firebase alternative

Open-source Firebase alternative providing a full backend-as-a-service on PostgreSQL. Auto-generated REST and GraphQL APIs from your schema, real-time subscriptions, built-in auth with 20+ social providers and Row Level Security, S3-compatible file storage with CDN, and Deno-powered Edge Functions. Visual dashboard with SQL editor and table editor. Supports pgvector for AI apps. Self-hostable or managed with a generous free tier. 75K+ GitHub stars.