Jelly-Patch: a Fast Format for Recording Changes in RDF Datasets
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866918139291238400 |
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| author | Sowinski, Piotr Grzymkowski, Kacper Danilenka, Anastasiya |
| author_facet | Sowinski, Piotr Grzymkowski, Kacper Danilenka, Anastasiya |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_23499 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Jelly-Patch: a Fast Format for Recording Changes in RDF Datasets Sowinski, Piotr Grzymkowski, Kacper Danilenka, Anastasiya Databases 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. |
| title | Jelly-Patch: a Fast Format for Recording Changes in RDF Datasets |
| topic | Databases |
| url | https://arxiv.org/abs/2507.23499 |