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UID:submissions.supercomputing.org_SC25_sess527_post221@linklings.com
SUMMARY:ScODA: An Emerging Pipeline for Evaluating Distributed Database Pe
 rformance To Support Operational Data Analytics
DESCRIPTION:Nicholas Synovic (Loyola University Chicago); FNU Shilpika, Si
 lvio Rizzi, and Doug Waldron (Argonne National Laboratory (ANL)); George K
 . Thiruvathukal (Loyola University Chicago); and Michael E. Papka (Argonne
  National Laboratory (ANL))\n\nAs high performance computing (HPC) systems
  scale toward the exascale era, operational data analytics (ODA) play an i
 ncreasingly central role in managing system security, health, scheduling, 
 and scientific productivity. Supercomputing facilities continuously genera
 te massive volumes of logs and system metrics. To make actionable insights
 , distributed database management systems (DBMSs) are often employed, but 
 their behavior under realistic production HPC workloads remains underexplo
 red. This poster presents ScODA (Supercomputing Operational Data Analytics
 ), an emerging benchmarking pipeline designed to evaluate distributed DBMS
  solutions—including relational, document, time-series databases and lakeh
 ouse solutions—using real and synthetic HPC environment logs. By working a
 longside our business intelligence colleagues to systematically model and 
 implement common ODA workflows, ScODA enables data-driven comparisons of c
 ompeting DBMS platforms and identifies trade-offs in ingestion, querying, 
 and concurrent access. We present our methodology, preliminary benchmarks,
  and lessons learned from applying ScODA to multiple DBMS platforms at Arg
 onne National Laboratory.\n\nTag: Research & ACM SRC Posters\n\nRegistrati
 on Category: Technical Program Reg Pass\n\nSession Chairs: Kento Sato (RIK
 EN Center for Computational Science (R-CCS)); Chris Schlipalius (Pawsey Su
 percomputing Research Centre; Commonwealth Scientific and Industrial Resea
 rch Organisation (CSIRO), Australia); and Anja Gerbes (Georg-August-Univer
 sität Göttingen)\n\n
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