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 applications. In a previous paper we have proposed an original approach to OLAP on document stores; its basic idea was to stop fighting against schema variety and welcome it as an inherent source of information wealth in schemaless sources. In this paper we focus on the querying phase, showing how queries can be directly rewritten on a heterogeneous collection in an inclusive way, i.e., also including the concepts present in a subset of documents only
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
Within the Big Data trend, there is an increasing interest in Not-only-SQL systems (NoSQL). These sy...
Document stores are preferred to relational ones for storing heterogeneous data due to their schemal...
none3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
open3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
OLAP has been extensively used for a couple of decades as a data analysis approach to support decisi...
NoSQL databases are preferred to relational ones for stor- ing heterogeneous data with variable sche...
Documents are a pervasive semi-structured data model in today's web and internet of things applicati...
The success of NoSQL DBMSs has pushed the adoption of polyglot storage systems that take advantage o...
International audienceNoSQL document stores are well-tailored to efficiently load and manage massive...
The growing use of document stores has resulted in vast amounts of semi-structured data holding prec...
International audienceNoSQL document stores offer native support to efficiently store documents with...
Not only SQL (NoSQL) databases are becoming increasingly popular and have some interesting strengths...
none4siMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heter...
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
Within the Big Data trend, there is an increasing interest in Not-only-SQL systems (NoSQL). These sy...
Document stores are preferred to relational ones for storing heterogeneous data due to their schemal...
none3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
open3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
OLAP has been extensively used for a couple of decades as a data analysis approach to support decisi...
NoSQL databases are preferred to relational ones for stor- ing heterogeneous data with variable sche...
Documents are a pervasive semi-structured data model in today's web and internet of things applicati...
The success of NoSQL DBMSs has pushed the adoption of polyglot storage systems that take advantage o...
International audienceNoSQL document stores are well-tailored to efficiently load and manage massive...
The growing use of document stores has resulted in vast amounts of semi-structured data holding prec...
International audienceNoSQL document stores offer native support to efficiently store documents with...
Not only SQL (NoSQL) databases are becoming increasingly popular and have some interesting strengths...
none4siMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heter...
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
Within the Big Data trend, there is an increasing interest in Not-only-SQL systems (NoSQL). These sy...