Publication | Closed Access
DBSherlock
73
Citations
40
References
2016
Year
Unknown Venue
Oltp DatabasesEngineeringData ScienceBusiness IntelligenceTransactional ApplicationDatabase ProcessingOnline Transaction ProcessingManagementTransactional SystemData IntegrationDatabase ScalabilityTransaction ProcessingComputer ScienceBusiness AnalyticsOltp Performance ProblemsData ManagementBig Data
OLTP databases are critical for real‑time business applications, yet performance problems—stemming from many concurrent transactions and shifting workloads—are hard to diagnose and can severely harm revenue and user experience. DBAs continuously monitor, diagnose, and rectify OLTP performance decays.
Running an online transaction processing (OLTP) system is one of the most daunting tasks required of database administrators (DBAs). As businesses rely on OLTP databases to support their mission-critical and real-time applications, poor database performance directly impacts their revenue and user experience. As a result, DBAs constantly monitor, diagnose, and rectify any performance decays. Unfortunately, the manual process of debugging and diagnosing OLTP performance problems is extremely tedious and non-trivial. Rather than being caused by a single slow query, performance problems in OLTP databases are often due to a large number of concurrent and competing transactions adding up to compounded, non-linear effects that are difficult to isolate. Sudden changes in request volume, transactional patterns, network traffic, or data distribution can cause previously abundant resources to become scarce, and the performance to plummet.
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