SQL and relational database systems (RDBMS) have been used and have evolved so closely that RDBMS is sometimes referred to as the SQL database, much to the chagrin of the theorists. Relational calculus and theory provided foundation for data modeling and manipulation. SQL provided applications and ad-hoc users, an easy way to define schema and manipulate the data. Its declarative nature, drivers, language bindings, and integration with multitude tools has made SQL indispensable. Even with the absence of SQL, NoSQL systems have become successful. Lack of SQL implies joins and advanced aggregations are absent. These are not the operations you can crank out with an all-nighter or two. The issues of scalability (#ScaleOutNotScaleUp), lack of hierarchical and flexible data model are severe in RDBMS. NoSQL applications work around this issue using various techniques like denormalization (to avoid joins), duplication or summarization of data to support variet...
A blog about all things data and data processing issues and interests. SQL, NoSQL, flexible schema, scale-up, scale-out, transactions, high availability.