Nov 3, 2024 · This study focuses on comparing two popular distributed graph processing frameworks: Apache Spark GraphX and Apache Flink. Both systems are popular, since they …

Apr 9, 2021 · The dimensions we detail encompass paradigms to express graph processing, different types of systems to use, coordination and communication models in distributed graph …

Feb 18, 2025 · Graph Analytics equips organizations to uncover insights from relationships between entities much faster. The full potential of knowledge graphs is untapped yet, as it is in …

Feb 26, 2017 · In this chapter, we survey current system approaches for management and analysis of “big graph data”. We discuss graph database systems, distributed graph …

In this review study, we have highlighted the importance of GSP for the processing of large datasets from the perspective of big data. We have discussed, basic graph signal processing …

compares open source solutions for processing large volumes of graph data. The growth of graph-structured data in modern applications such as social networks and knowledge bases …

In this paper, we evaluate and compare GraphX based on Spark and Gelly based on Flink as two prominent graph processing frameworks. We focus on the scalability of GraphX and Gelly with …

Jan 1, 2019 · On the one hand, the basic computation entity in a GPF can be graph-centric, vertex-centric, or edge-centric. On the other hand, as big data drives graph sizes beyond …

May 26, 2020 · We categorize the benchmarks into three areas focusing on benchmarks for graph processing systems, graph database benchmarks, and bigdata benchmarks with graph …

How can we do better, leveraging GraphLab’s consistency mechanisms? Async. Snapshot Performance. incurred from the slow machine! Step 1. Atomically one initiator. Step 2. On …