none3noSchemaless databases, and document-oriented databases in particular, are preferred to relational ones for storing heterogeneous data with variable schemas and structural forms. However, the absence of a unique schema adds complexity to analytical applications, in which a single analysis often involves large sets of data with different schemas. In this paper we propose an original approach to OLAP on collections stored in document-oriented databases. The basic idea is to stop fighting against schema variety and welcome it as an inherent source of information wealth in schemaless sources. Our approach builds on four stages: schema extraction, schema integration, FD enrichment, and querying; these stages are discussed in detail in the p...
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential eleme...
OLAP has been extensively used for a couple of decades as a data analysis approach to support decisi...
open3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
Document stores are preferred to relational ones for storing heterogeneous data due to their schemal...
open3noIn document-oriented databases, schema is a soft concept and the documents in a collection ca...
none4siMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heter...
NoSQL databases are preferred to relational ones for stor- ing heterogeneous data with variable sche...
In document-oriented databases, schema is a soft concept and the documents in a collection can be st...
none4siThe success of NoSQL DBMSs has pushed the adoption of polyglot storage systems that take adva...
The velocity, variety, and volume of present-day data bring about new problems that Database Managem...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
The growing use of document stores has resulted in vast amounts of semi-structured data holding prec...
The emergence of applications that manage very large volumes of semi-structured data is driving the ...
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential eleme...
OLAP has been extensively used for a couple of decades as a data analysis approach to support decisi...
open3noSchemaless databases, and document-oriented databases in particular, are preferred to relatio...
Document stores are preferred to relational ones for storing heterogeneous data due to their schemal...
open3noIn document-oriented databases, schema is a soft concept and the documents in a collection ca...
none4siMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamlessly query heter...
NoSQL databases are preferred to relational ones for stor- ing heterogeneous data with variable sche...
In document-oriented databases, schema is a soft concept and the documents in a collection can be st...
none4siThe success of NoSQL DBMSs has pushed the adoption of polyglot storage systems that take adva...
The velocity, variety, and volume of present-day data bring about new problems that Database Managem...
International audienceMulti-model DBMSs (MMDBMSs) have been recently introduced to store and seamles...
The growing use of document stores has resulted in vast amounts of semi-structured data holding prec...
The emergence of applications that manage very large volumes of semi-structured data is driving the ...
Recent approaches adopt multimodel databases (MMDBs) to natively handle the variety issues arising f...
On-Line Analytical Processing (OLAP) systems based on multidimensional databases are essential eleme...
OLAP has been extensively used for a couple of decades as a data analysis approach to support decisi...