Graph Database Performance Comparison

Graph Database Performance Comparison Test Results. The Tencent Cloud Security team has used graph data at different orders of magnitudes for testing purpose. The test has been performed against various metrics, including data import efficiency, one-hop query, two-hop query, and shared friends query. The results are as below

Discover the leading graph databases in the dynamic landscape of data management. Our comprehensive guide compares and analyzes top players like Neo4j, Amazon Neptune, ArangoDB, and Nebula, providing insights into features, use cases, and industry applications. Best Suited For Projects needing a high-performance, distributed graph database

Amazon Web Services. Platform Amazon Neptune Description Amazon Neptune is a fully-managed graph database service that lets you build and run applications that work with highly connected datasets.The foundation for Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph quickly.

Previous similar efforts have fallen short in providing a complete evaluation of graph databases, and drawing a clear picture on how they compare to each other. We introduce a micro-benchmarking framework for the assessment of the functionalities of the existing systems and provide detailed insights on their performance.

The right graph database can make or break your project. DB-Engines is a valuable resource for developers and data professionals seeking to evaluate and compare various database management systems. It provides comprehensive information and rankings for over 350 database systems, including both relational SQL and non-relational NoSQL

To our knowledge only a handful of researches on graph databases performance has been conducted. The Neo4j organization has made an official performance comparison testing for several graph algorithms covered by its graph algorithms library .Paper provides a comparative analysis of the Neo4j graph database with the relational database MySQL.

The data schema follows the property graph data model. Measurements during the benchmark, which we believe to be the first benchmark test using the LDBC-SNB SF-30K BI workload on a distributed graph database, included loading time, storage size, and query latency of the 20 BI queries on a cluster of 40 machines.

One of the main advantages of the graph database is its effective performance in data queries. This paper presents a comprehensive comparison of the performance based on the execution time of a NoSQL graph database named Neo4J with a popular relational database system, MySQL, which is used as the underlying technology in developing a software

We aim to present a comprehensive comparison between a graph database, Neo4j, and a relational database, MySQL, focusing on their performance based on different types of queries.

Previous studies where the performance of graph databases, especially Neo4j, was compared with the traditional SQL databases, indicate that graph databases possess better performance than relational databases. However, those studies mainly focused on quite simple queries. In contrast to the earlier studies, researchers investigated the performance of database systems in