Performance Evaluation of NoSQL Databases: A Case Study

Abstract

The choice of a particular NoSQL database imposes a specific distributed software architecture and data model, and is a major determinant of the overall system throughput. NoSQL database performance is in turn strongly influenced by how well the data model and query capabilities fit the application use cases, and so system-specific testing and characterization is required. This paper presents a method and the results of a study that selected among three NoSQL databases for a large, distributed healthcare organization. While the method and study considered consistency, availability, and partition tolerance (CAP) tradeoffs, and other quality attributes that influence the selection decision, this paper reports on the performance evaluation method and results. In our testing, a typical workload and configuration produced throughput that varied from 225 to 3200 operations per second between database products, while read operation latency varied by a factor of 5 and write latency by a factor of 4 (with the highest throughput product delivering the highest latency). We also found that achieving strong consistency reduced throughput by 10-25% compared to eventual consistency.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2015
Accession Number
ADA614628

Entities

People

  • Chrisjan Matser
  • Ian Gorton
  • John Klein
  • Kim Pham
  • Neil Ernst
  • Patrick Donohoe

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Abstracts
  • Availability
  • Big Data
  • Case Studies
  • Consistency
  • Data Centers
  • Data Sets
  • Databases
  • Engineering
  • Governments
  • Measurement
  • Software Design
  • Software Development
  • Test And Evaluation
  • Throughput
  • United States Government
  • Workload

Fields of Study

  • Computer science

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation
  • Database Systems and Applications