Data Management for High-Throughput Genomics
Summary: Proposes using relational DB (SQL Server) as the primary storage and processing platform for high-throughput sequencing workloads, addressing tens of TB/week of data. Describes a DB schema, unconventional storage tricks, and leveraging SQL/UDFs for in‑database analysis with initial scalability and performance findings. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Uwe Röhm
- 2. José A. Blakeley
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 974 | The POSTGRES Data Model | 1987 | VLDB | 0.00014896625 |
| 6,023 | Hosting the .NET Runtime in Microsoft SQL Server | 2004 | SIGMOD | 5.2415551e-05 |
| 12,367 | .NET Database Programmability and Extensibility in Microsoft SQL Server | 2008 | SIGMOD | 4.1945683e-05 |
Previous
Page 1 / 1
Next