Awesome GitHub RepositoriesPluggable Storage Backends

Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels. The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges. Query capabilities cover bidirectional path traversal and multi-syntax execution usi

Gorse is a personalized recommendation engine server and machine learning pipeline designed to suggest items to users based on their behavior and preferences. It operates as a distributed system that separates training, candidate generation, and serving nodes to support high-throughput workloads. The system utilizes a multi-stage recommendation pipeline to refine results through retrieval, scoring, and reranking. It generates personalized suggestions using collaborative filtering, matrix factorization, and item-to-item similarity models, while also providing non-personalized and fallback reco

JanusGraph is a distributed, elastically scalable graph database designed to store and query highly connected data across a cluster of machines. It supports the property graph data model with ACID consistency and integrates multi-model search capabilities including geo, numeric range, and full-text queries. The database also includes a Graph OLAP engine for running batch analytics and global graph computations on large datasets using the Hadoop framework. The project distinguishes itself through a masterless cluster architecture that eliminates single points of failure, allowing every node to

Titan is a distributed graph database and computing engine designed for storing and querying massive datasets of interconnected nodes and edges across multi-machine clusters. It functions as a scalable graph storage layer and transactional store, providing a framework for executing large-scale graph processing jobs and deep traversals. The system is distinguished by its pluggable storage backend, which decouples the graph engine from the physical persistence layer. It utilizes vertex-cut data partitioning to balance processing loads and a set-cardinality property model that allows single prop

nano-graphrag 是一个检索系统，使用知识图谱为大语言模型响应提供结构化上下文。它既是一个将非结构化文本转换为实体和关系网络的知识图谱索引器，也是一个混合图检索系统。 该项目通过结合局部邻域搜索和全局社区摘要来回答复杂的自然语言问题，从而脱颖而出。它包含一个知识图谱可视化工具，可生成实体及其关系的 HTML 表示，以映射索引知识。 该框架涵盖了广泛的功能，包括实体关系提取、基于社区的图聚类和基于哈希的增量索引。它提供了一个集成层，用于连接开源模型和本地嵌入提供程序，并支持用于键值、向量和图数据的可插拔存储后端。通过基于参数的响应缓存和用于修复语言模型不稳定 JSON 输出的后处理函数，提供了额外的实用性。