2 个仓库
Large-scale computation specifically focused on identifying patterns and performing deep traversals in massive graphs.
Distinct from Large-Scale Data Computation: Distinct from Large-Scale Data Computation: specializes in graph-specific analytic patterns and deep traversals rather than general data processing.
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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
Executes complex processing jobs and deep traversals across billions of vertices to find patterns in big data.
Kùzu is an embedded property graph database engine designed for high-performance analytical queries and local data management. It operates as a library within the host application process, utilizing a columnar-based storage architecture and just-in-time query compilation to execute complex graph traversals and pattern matching efficiently. By mapping database files directly into system memory, it ensures data durability and high-speed access while maintaining ACID-compliant transactional integrity. The engine distinguishes itself by integrating vector similarity search and full-text search di
Executes advanced graph algorithms like PageRank and community detection for deep data analysis.