![]() ![]() These considerations cause us to change our data modeling approach from the traditional constraints of RDBMS(schema on write) to modeling data for the specific application (schema on read).Īnother differentiator between RDBMS and NoSQL systems which impact modeling paradigms is the concept of normalization and denormalization of data. Modeling for NoSQL on the other hand, explores application specific access patterns e.g., “what are the types of questions users would like to answer with this data?” This in turn dictates the kind of queries that need to be supported and focuses on how best to lay out the data for performance optimization. Traditionally, data modeling for relational systems was the science of identifying the data objects, their relationships with one another, and their accurate representation, that laid the foundation for a good database design. Infact, data modeling is often a critical success factor to Couchbase deployments, and progressively optimizing data models can be a huge application performance booster given the rapidly evolving nature of big data applications.
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