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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.10886 |
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| _version_ | 1866912427238490112 |
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| author | Vasquez-Grinnell, Steven Poliakov, Alex |
| author_facet | Vasquez-Grinnell, Steven Poliakov, Alex |
| contents | To meet the needs of a large pharmaceutical organization, we set out to create S3Mirror - an application for transferring large genomic sequencing datasets between S3 buckets quickly, reliably, and observably. We used the DBOS Transact durable execution framework to achieve these goals and benchmarked the performance and cost of the application. S3Mirror is an open source DBOS Python application that can run in a variety of environments, including DBOS Cloud Pro, where it runs as much as 40x faster than AWS DataSync at a fraction of the cost. Moreover, S3Mirror is resilient to failures and allows for real-time filewise observability of ongoing and past transfers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_10886 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | S3Mirror: Making Genomic Data Transfers Fast, Reliable, and Observable with DBOS Vasquez-Grinnell, Steven Poliakov, Alex Databases Genomics To meet the needs of a large pharmaceutical organization, we set out to create S3Mirror - an application for transferring large genomic sequencing datasets between S3 buckets quickly, reliably, and observably. We used the DBOS Transact durable execution framework to achieve these goals and benchmarked the performance and cost of the application. S3Mirror is an open source DBOS Python application that can run in a variety of environments, including DBOS Cloud Pro, where it runs as much as 40x faster than AWS DataSync at a fraction of the cost. Moreover, S3Mirror is resilient to failures and allows for real-time filewise observability of ongoing and past transfers. |
| title | S3Mirror: Making Genomic Data Transfers Fast, Reliable, and Observable with DBOS |
| topic | Databases Genomics |
| url | https://arxiv.org/abs/2506.10886 |