Catching up with Disorder: Dynamic Graphs with Out-of-Order Updates

Several real-time applications rely on dynamic graphs to model and store data arriving from multiple streams, potentially distributed. Providing both high ingestion rate and efficient analytics with transactional guarantees over such dynamic graphs is challenging, even more so when updates may be received out-of-order at the database. We propose to demonstrate HAL [2], a novel in-memory dynamic graph database system, which addresses these challenges. HAL outperforms comparable systems by a factor of up to 73× in terms of update processing throughput and up to 357× for analytics, while being the first to support out-of-order updates.