NoSQL Data Store Technologies

Abstract

The Interagency Program Office has been exploring a number of options for interoperation between the electronic health record systems used by DoD and the Veteran's Health Administration. These have included replacing both systems with a single new Integrated Electronic Health Record (iEHR) system and federating the information contained in existing systems, among other approaches. In addition, DoD has been exploring caching approaches to improve delivery of electronic health record applications over network links with low quality of service. The Military Health System's Joint Program Committee funded the Army Telemedicine and Advanced Technology Research Center (TATRC) to work with the SEI to investigate the use of emerging NoSQL database technology to achieve the data storage capabilities needed for these systems. The SEI conducted a stakeholder workshop with MHS stakeholders to identify architecture drivers and quality attribute requirements for these applications. These requirements were then used to create technology evaluation criteria. The SEI then worked with developers from the TATRC Advanced Concepts Team to conduct a series of technology experiments to assess the suitability of several NoSQL products against the evaluation criteria. One NoSQL product was selected for evaluation from each of the four NoSQL categories: Document Store (MongoDB), Column Family Store (Cassandra), Key-Value Store (Riak), and Graph Store (Neo4J). Each product was installed in a server cluster in the SEI Virtual Private Cloud, and performance measurements were made for each using the YCSB (Yahoo! Cloud Serving Benchmark) test driver. Several workloads were tested, including read-only, write-only, bulk load, and mixed read/write. Testing was also conducted to assess performance of the server cluster when there are network delays or partitions.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2014
Accession Number
ADA611676

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

  • Big Data
  • Computer Programming
  • Computers
  • Data Analysis
  • Data Centers
  • Data Processing
  • Data Sets
  • Data Storage Systems
  • Databases
  • Department Of Defense
  • Information Science
  • Information Systems
  • Lessons Learned
  • Mobile Devices
  • Operating Systems
  • Software Development
  • Spreadsheet Software

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Medical or Health Care Field.
  • Parallel and Distributed Computing.

Technology Areas

  • Microelectronics