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The Value of Multi-Model Databases

Relational database technology first appeared almost a half-century ago and for decades the database market appeared to be consolidating around the use of relational databases for most types of workloads, even if it wasn’t very well suited to some of these workloads. More recently, though, as the big data market has exploded organizations have become less reliant on relational databases and appear more willing to use a variety of other database technologies including NoSQL databases to support their data processing needs.

As additional data models gained favor, relational database vendors responded by expanding their products to support a variety of data models, including multidimensional, document, in-memory, NoSQL, graph and others. Our research over the past five years shows widespread acceptance of multiple data model deployments. During this time, our research shows that the percentage of enterprises using different types of database technologies has remained relatively steady, and 40 percent of organizations have adopted a multi-model approach to their data processing needs involving two or more database technologies.


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About the Author


David Menninger

SVP and Research Director
Ventana Research

David Menninger is responsible for the overall direction of research on data and analytics technologies at Ventana Research. He covers major areas including artificial learning and machine learning, big data, business intelligence, collaboration, data science and information management along with the additional specific research categories including blockchain, data governance, data lakes, data preparation, embedded analytics, natural language processing (NLP) and IoT.