Graph Pattern Matching

A Graph-Native Query Optimization Framework

GOpt is built on top of a unified intermediate representation (IR) that is capable of capturing both graph and relational operations, thereby streamlining the optimization of graph queries.

A High-Throughput Transactional Graph Database

GraphScope Interactive is a specialized construction of GraphScope Flex, designed to handle concurrent graph queries at an impressive speed. Its primary goal is to process as many queries as possible within a given timeframe, emphasizing a high query throughput rate.

Interactive Graph Pattern Matching

We develop GLogS system, allowing users to interactively submit queries using a declarative language, which will be compiled and automatically optimized, and eventually executed on the GAIA dataflow engine.

Towards a Converged Relational-Graph Optimization Framework

The recent ISO SQL:2023 standard adopts SQL/PGQ (Property Graph Queries), facilitating graph-like querying within relational databases. This advancement, however, underscores a significant gap in how to effectively optimize SQL/PGQ queries within …

GLogS: Interactive Graph Pattern Matching Query At Large Scale

Interactive GPM (iGPM) is becoming increasingly important for data scientists to explore graphs in real life, where a series of graph pattern matching (GPM) queries are created and submitted in an interactive manner based on the insights provided by …

PatMat: A Distributed Pattern Matching Engine with Cypher

Graph pattern matching is one of the most fundamental problems in graph database and is associated with a wide spectrum of applications. Due to its computational intensiveness, researchers have primarily devoted their efforts to improving the …

Distributed Pattern Matching System with Cypher

To develop a graph pattern matching system in the distributed context, while gluing together the academic results of optimal join algorithms and industrial efforts of query language