How Many IOPS is Enough?

How Many IOPS is Enough?

IT professionals find it difficult to determine which SSD or flash array to buy or even whether they can get the speed they need from standard HDDs. There is an extraordinarily wide rage of IOPS (from hundreds to millions), latencies, and capacities, and this can be confusing. This 2017 update to our rigorous 2012 report provides, through a survey of nearly 260 IT managers and other end users, a good understanding of the needs of various applications including IOPS, latency, and capacity.

The 157-page report, jointly produced by Objective Analysis and Coughlin Associates, dissects the results of a months-long on-line survey of IT managers which collected their inputs on the IOPS, capacity, and latency needs for a number of key enterprise applications. Through its 136 figures and eight tables the study sheds new light on the speed requirements for certain key applications like OLTP, database management, and cloud services.

Executive Summary
Survey Objective
Why Did We Do This?
Margin of Error
Anticipated Outcome
Storage Devices and their Characteristics
SSDs and Flash Memory vs DRAM
Caching/Tiering vs Determinism
Raw Data Analysis
IOPS Requirements
Capacity Requirements
Impact of Other System Bottlenecks
Minimum Useful Latency
Comparing the Results
IOPS vs Capacity
Latency vs Capacity
IOPS vs Latency
Application Sensitivities
Database Systems
Metadata Servers
Data Warehousing and Search
Internet Server Caching
On Line Transaction Processing (OLTP)
Charge Card Processing
Reservations Systems
Algorithmic Trading
Currency Exchange and Arbitrage
Inter-Bank Transfers
Other On-Line Transaction Processing Applications
Cloud or Storage Services
Real Time Data/Feed Processing
Contextual Web Advertising
Scientific or Engineering Applications
Electronic Design Automation & Modeling
Weather/Life Sciences
Aerodynamics Design
Nuclear Fission Models
Software Development
IOPS Requirements by Application
The Monetary Value of Higher IOPS Figures
How the Market Should Develop
Appendix A: The Online Survey
Appendix B: Data Inconsistencies
Possible Reasons for Inconsistencies
Jim Handy
Tom Coughlin

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