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DNA microarrays, which allow for the parallel analysis of thousands of genes, have become the most popular functional genomic tool in use today. Substantial data sets are currently being produced by researchers in both the public and the private sector. Proceeding at a significantly slower rate than its complement, microarray data generation, the analysis of microarray data is a true bottleneck for research. The situation will only become more serious in the future, as DNA microarray technology becomes less expensive and projects increase both in number and in size. Clearly, in order to realize the full promise of microarray technology, bioinformatics solutions must evolve. The research microarray database is a crucial step in the evolution of bioinformatics software for modern genomic-scale science. The role of the research microarray database is to support microarray data analysis in the context of a collaborative research environment. At the current stage of microarray research, there are four principal requirements a microarray research database should satisfy. It must be able to store microarray data, store the annotation of the data, store a detailed record of the tasks performed while working with the data, and support research collaboration. Each of the four requirements presents challenges of its own. In conclusion, relational database management systems (DBMSs) have been under active, intensive development for over 20 years. In these two decades, the challenges and issues discussed here have been addressed by the designers of relational database engines. State-of-the-art security features are built into every major DMBS, allowing users to share data safely in a multi-user environment, such as the Internet. Advanced concurrency control ensures data integrity and consistency. A DBMS is the ideal solution for the Internet-connected world of research and data analysis.