Analyzing Lightning Network Payment Channels with Memgraph

Vincent, a Senior Data Scientist from Amboss Technologies, shared his insights during a Memgraph Community Call on using Memgraph to analyze the Lightning Network, a layer 2 payment protocol built on the Bitcoin blockchain to facilitate faster and cheaper transactions. He highlighted Memgraph's in-memory capabilities for real-time analysis, which provide sub-second latency essential for pathfinding queries and make it a superior choice over other graph databases. Vincent's personal project, LN Stream, loads and streams data from the Lightning Network into Memgraph, allowing real-time analysis and visualization of network characteristics such as node capacity, fee ratios, and payment paths using Memgraph Lab. He demonstrated various queries that extract meaningful insights from the data, emphasizing the value of Memgraph's features like lambda expressions and conditional expansion for efficient pathfinding. During the Q&A session, Vincent offered advice on automating repetitive tasks, and he discussed future project directions focused on pathfinding and channel balance prediction, highlighting the ongoing need for research and collaboration.