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DTSTART;TZID=America/Denver:20231115T100000
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UID:submissions.supercomputing.org_SC23_sess299_spostg124@linklings.com
SUMMARY:Accelerating CRUD with Chrono Dilation for Time-Series Storage Sys
 tems
DESCRIPTION:Lan Nguyen (Illinois Institute of Technology)\n\nIn recent yea
 rs, we have seen an un-precedented growth of data in our daily lives rangi
 ng from health data from an Apple Watch, financial stock price data, volat
 ile crypto-currency data, to diagnostic data of nuclear/rocket simulations
 . The increase in high-precision, high-sample-rate time-series data is a c
 hallenge to existing database technologies. We have developed a novel tech
 nique that utilizes sparse-file support to achieve O(1) time complexity in
  create, read, update, and delete (CRUD) operations while supporting time 
 granularity down to 1-second. We designed and implemented XStore to be lig
 htweight and offer high performance without the need to maintain an index 
 of the time-series data. We have conducted a detailed evaluation between X
 Store and existing best-of-breed systems such as MongoDB using synthetic d
 ata spanning 20 years, with second granularity, totaling over 5 billion da
 tapoints. Through empirical experiments against MongoDB, XStore achieves 2
 .5X better latency and delivers up to 3X improvement in throughput.\n\nTag
 : Artificial Intelligence/Machine Learning, Algorithms, Applications, Arch
 itecture and Networks, Cloud Computing, Distributed Computing, Data Analys
 is, Visualization, and Storage, Performance Measurement, Modeling, and Too
 ls, Programming Frameworks and System Software\n\nRegistration Category: T
 ech Program Reg Pass, Exhibits Reg Pass\n\n
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