Graph databases (GDBs) are crucial in academic and industry applications. The key
challenges in develo** GDBs are achieving high performance, scalability …

GeaFlow is a distributed dataflow system optimized for streaming graph processing, and has
been widely adopted at Ant Group, serving various scenarios ranging from risk control of …

Distributed persistent key-value store (KVS) plays an important role in today's storage
infrastructure. The development of persistent memory (PM) and remote direct memory …

Graph partitioning plays a pivotal role in various distributed graph processing applications,
including graph analytics, graph neural network training, and distributed graph databases …

We introduce Galaxybase, a native distributed graph database that addresses the
increasing demands for processing large volumes of graph data in diverse industries like …

Based on the diversified application scenarios at Ant Group, we built the Ant Knowledge
Graph Platform (AKGP). It has constructed numerous domain-specific knowledge graphs …

Regular path queries (RPQs) in graph databases are bottlenecked by the memory wall.
Emerging processing-in-memory (PIM) technologies offer a promising solution to dispatch …

There is a proliferation of applications requiring the management of large-scale, evolving
graphs under workloads with intensive graph updates and lookups. Driven by this …

ByteDance's products, including TikTok, Douyin, and Toutiao, generate massive amounts of
graph data every day. Previously, we developed ByteGraph, a distributed graph database …

The effectiveness of in-memory dynamic graph storage (DGS) for supporting concurrent
graph read and write queries is crucial for real-time graph analytics and updates. Various …