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Review of open-source software for developing heterogeneous data management systems for bioinformatics applications.

Danilo Silva^1,2, Monika Moir¹, Marcel Dunaiski^2,3

¹Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, 7602, South Africa.

Bioinformatics Advances

|August 5, 2025

Summary

This summary is machine-generated.

Bioinformatics researchers face data management challenges. This study explores the data lakehouse, a novel approach combining data lake flexibility with data warehouse governance, for efficient heterogeneous data handling in health sciences.

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Area of Science:

Bioinformatics and Health Sciences Data Management

Background:

Researchers in bioinformatics and health sciences struggle with managing diverse and complex datasets.
Existing solutions like non-relational databases and data warehouses lack the required flexibility and scalability.
Data lakes offer flexibility but lack robust governance, hindering effective data management.

Purpose of the Study:

To explore the data lakehouse paradigm as a solution for managing heterogeneous data in bioinformatics.
To review strategies and tools for developing a data lakehouse infrastructure tailored to bioinformatics research.
To assess available open-source and commercial solutions for bioinformatics data management.

Main Methods:

Review of existing data management strategies and tools.
Conceptual assessment of the data lakehouse model for bioinformatics applications.
Evaluation of open-source and commercial solutions relevant to data lakehouse implementation.

Main Results:

The data lakehouse paradigm presents a promising solution by integrating data lake flexibility with data warehouse governance.
Limited literature currently exists on applying the data lakehouse model within the bioinformatics domain.
A review of strategies and tools for developing such infrastructure is presented.

Conclusions:

The data lakehouse offers a potentially powerful framework for addressing the complexities of bioinformatics data management.
Further research and development are needed to fully explore and implement lakehouse solutions in bioinformatics.
This review provides a foundational understanding of concepts and tools for bioinformatics data lakehouse development.