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Relational Databases and Biomedical Big Data.

N H Nisansa D de Silva1

  • 1Department of Computer and Information Science, University of Oregon, 224 Deschutes Hall, 1477 E 13th Ave., Eugene, OR, 97403, USA. nisansa@cs.uoregon.edu.

Methods in Molecular Biology (Clifton, N.J.)
|May 26, 2017
PubMed
Summary
This summary is machine-generated.

Biomedical big data presents challenges for traditional relational databases. This review examines the advantages and disadvantages of using relational databases for managing large-scale biomedical data.

Keywords:
Big dataBiomedical big dataData miningRelational databases

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Area of Science:

  • Biomedical Informatics
  • Data Management

Background:

  • Biomedical applications generate vast amounts of data, reaching 'big data' levels.
  • Relational databases have been the traditional choice for managing biomedical data.
  • There is a growing trend towards alternative database solutions in the biomedical field.

Purpose of the Study:

  • To review the pros and cons of using relational databases for biomedical big data.
  • To understand the interrelation between biomedical big data and relational database technology.

Main Methods:

  • Literature review of previous research on relational databases and biomedical big data.
  • Analysis of discussed advantages and disadvantages.

Main Results:

  • Relational databases offer structured data management but can face scalability issues with big data.
  • Understanding their limitations is crucial for effective data handling in biomedical research.

Conclusions:

  • While relational databases have served the biomedical field, their suitability for big data requires careful consideration.
  • The review highlights the need to weigh the benefits against the drawbacks of relational databases in the context of growing biomedical datasets.