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A comparison of database systems for XML-type data.
Judith E Risse1, Jack A M Leunissen
1Laboratory for Bioinformatics, Wageningen University and Research Centre, Wageningen, The Netherlands.
In Silico Biology
|March 21, 2012
Summary
Choosing the right database for large XML datasets like Medline is crucial. Performance varies significantly with dataset size, with Oracle 11g and Lingpipe offering robust solutions, while Sedna, BaseX, and MySQL suit evolving data structures.
Area of Science:
- Bioinformatics
- Database Management
- Computational Biology
Background:
- Extensible Markup Language (XML) is prevalent in bioinformatics and web services.
- The growing volume of XML data necessitates efficient storage and querying solutions.
- Analysis focuses on suitability of various database systems for large-scale XML datasets, specifically Medline.
Purpose of the Study:
- To evaluate and compare the performance of different database systems for storing and querying large XML datasets.
- To identify optimal database solutions based on dataset size and specific query requirements.
Main Methods:
- Comparative analysis of multiple database systems.
- Testing with small, medium, and the full Medline XML dataset.
- Performance metrics focused on query execution times.
Main Results:
- All systems performed adequately on small to medium datasets.
- Significant variations in query times were observed when querying the full Medline dataset.
- No single system universally outperformed others across all scenarios.
Conclusions:
- Database system suitability depends on data size and query needs.
- Oracle 11g with binary storage is a strong all-round performer.
- Lingpipe offers a lightweight, customizable, and fast alternative, requiring more setup.
- Sedna, BaseX (native XML DBs), or MySQL (with XML-type column) are suitable for data with changing XML structures.
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