Abstract The success of NoSQL DBMSs has pushed the adoption of polyglot storage
systems that take advantage of the best characteristics of different technologies and data …

Schemaless databases, and document-oriented databases in particular, are preferred to
relational ones for storing heterogeneous data with variable schemas and structural forms …

The discipline of data science is steering analysts away from traditional data warehousing
and towards a more flexible and lightweight approach to data analysis. The idea is to …

In agile software development settings, applications are typically backed by schema-flexible
NoSQL databases. New application code frequently implies data model changes to the …

The schema flexibility of database management systems is often seen as an advantage,
because it makes it easy to store all kinds of different data. Schema-less database systems …

NoSQL document stores are well-tailored to efficiently load and manage massive collections
of heterogeneous documents without any prior structural validation. However, this flexibility …

NoSQL systems are based on a “schemaless” approach that not does require schema
specification before writing data, allowing a wide variety of representations. This flexibility …

Document stores are preferred to relational ones for storing heterogeneous data due to their
schemaless nature. However, the absence of a unique schema adds complexity to analytical …

NoSQL document stores offer native support to efficiently store documents with different
schema within a same collection. However, this flexibility made it difficult and complex to …

NoSQL database systems are useful for managing large and diverse data sets associated
with Big Data. Highly diverse data sets contain data with different structures, but often there …