{"ID":2888358,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.23499","arxiv_id":"2507.23499","title":"Jelly-Patch: a Fast Format for Recording Changes in RDF Datasets","abstract":"Recording data changes in RDF systems is a crucial capability, needed to support auditing, incremental backups, database replication, and event-driven workflows. In large-scale and low-latency RDF applications, the high volume and frequency of updates can cause performance bottlenecks in the serialization and transmission of changes. To alleviate this, we propose Jelly-Patch -- a high-performance, compressed binary serialization format for changes in RDF datasets. To evaluate its performance, we benchmark Jelly-Patch against existing RDF Patch formats, using two datasets representing different use cases (change data capture and IoT streams). Jelly-Patch is shown to achieve 3.5--8.9x better compression, and up to 2.5x and 4.6x higher throughput in serialization and parsing, respectively. These significant advancements in throughput and compression are expected to improve the performance of large-scale and low-latency RDF systems.","short_abstract":"Recording data changes in RDF systems is a crucial capability, needed to support auditing, incremental backups, database replication, and event-driven workflows. In large-scale and low-latency RDF applications, the high volume and frequency of updates can cause performance bottlenecks in the serialization and transmiss...","url_abs":"https://arxiv.org/abs/2507.23499","url_pdf":"https://arxiv.org/pdf/2507.23499v2","authors":"[\"Piotr Sowinski\",\"Kacper Grzymkowski\",\"Anastasiya Danilenka\"]","published":"2025-07-31T12:39:39Z","proceeding":"cs.DB","tasks":"[\"cs.DB\"]","methods":"[]","has_code":false}