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-# Unibench
-Towards Benchmarking Multi-Model DBMS
+# Unibench - Towards Benchmarking Multi-Model DBMS
+As more businesses realized that data, in all forms and sizes, is critical to making the best possible decisions, we see the continued growth of systems that support massive volume of relational or non-relational forms of data. Unlike traditional database management systems which are organized around a single data model that determines how data can be organized, stored, and manipulated, a multi-model database is designed to support multiple data models against a single, integrated backend. For example, document, graph, relational, and key-value models are examples of data models that may be supported by a multi-model database. Nothing shows the picture more starkly than looking at Gartner Magic quadrant for operational database management systems, which assumes that, by 2017, all leading operational DBMSs will offer multiple data models, relational and NoSQL, in a single DBMS platform. Having a single data platform for managing both well-structured data and NoSQL data is beneficial to users; this approach reduces significantly integration, migration, development, maintenance, and operational issues.
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