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

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.