The Experts below are selected from a list of 2112 Experts worldwide ranked by ideXlab platform
Wouter Joosen - One of the best experts on this subject based on the ideXlab platform.
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Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks
Information Systems, 2019Co-Authors: Vincent Reniers, Dimitri Van Landuyt, Ansar Rafique, Wouter JoosenAbstract:Abstract Context: Software applications frequently interact with Database systems to persist and retrieve objects. Object mapping frameworks address (i) the bi-directional conversion of data between object and target Database and (ii) provide a programmatic interface for querying and storing data. The rise of NoSQL Databases poses challenges beyond object-relational mapping (ORM) frameworks to abstract from various data models and non-standardized API’s, but also take into account the different Database capabilities (e.g. unsupported query operators, data ordering). Objective: A systematic survey study of existing Object-NoSQL data mapping (ONDM) frameworks. Specific focus is given to the level of abstraction of data and operations to multiple Database technologies, as a means to limit vendor and technology lock-in and an enabler for multi-store and polyglot architectures. Additional attention is paid to mapping strategies that are specific to NoSQL Databases (e.g. object embedding, schema flexibility). Method: A systematic search methodology identifies all relevant object mapping frameworks (in total 341 frameworks). Subsequently, a subset of ONDM frameworks is selected and systematically compared in terms of criteria of: Database support, interface and query functionality, architecture and software coupling. Secondly, we provide an in-depth comparison of object-oriented mapping strategies for classes, inheritance, relationships, and attribute types to NoSQL data models. Results: ONDM frameworks are most prevalent in Java, Node.JS, Python, and overall 54 frameworks support multiple (NoSQL) Databases. Interfaces are frequently standardized and commonly feature a uniform query language and even native DB query mapping. However, Database Portability may be hindered due to non-uniform abstractions. As for mapping strategies, current frameworks do not fully exploit NoSQL’s modeling potential, such as (i) the embedding of relationship data within referring objects’ records, (ii) mapping at the individual object-level vs. class-level, and (iii) lacking collection normalization despite being supported for associations or when using relational Databases. Conclusion: The study consolidates knowledge on available ONDM frameworks, and applied object-document, object-graph, and object-column mapping patterns. The study can guide practitioners in framework selection, and pinpoints areas of future development and research in this domain, most notably towards improved support for flexible, NoSQL-aware mapping strategies.
Joosen Wouter - One of the best experts on this subject based on the ideXlab platform.
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Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks
'Elsevier BV', 2019Co-Authors: Reniers Vincent, Van Landuyt Dimitri, Rafique Ansar, Joosen WouterAbstract:© 2019 Elsevier Ltd Context: Software applications frequently interact with Database systems to persist and retrieve objects. Object mapping frameworks address (i) the bi-directional conversion of data between object and target Database and (ii) provide a programmatic interface for querying and storing data. The rise of NoSQL Databases poses challenges beyond object-relational mapping (ORM) frameworks to abstract from various data models and non-standardized API's, but also take into account the different Database capabilities (e.g. unsupported query operators, data ordering). Objective: A systematic survey study of existing Object-NoSQL data mapping (ONDM) frameworks. Specific focus is given to the level of abstraction of data and operations to multiple Database technologies, as a means to limit vendor and technology lock-in and an enabler for multi-store and polyglot architectures. Additional attention is paid to mapping strategies that are specific to NoSQL Databases (e.g. object embedding, schema flexibility). Method: A systematic search methodology identifies all relevant object mapping frameworks (in total 341 frameworks). Subsequently, a subset of ONDM frameworks is selected and systematically compared in terms of criteria of: Database support, interface and query functionality, architecture and software coupling. Secondly, we provide an in-depth comparison of object-oriented mapping strategies for classes, inheritance, relationships, and attribute types to NoSQL data models. Results: ONDM frameworks are most prevalent in Java, Node.JS, Python, and overall 54 frameworks support multiple (NoSQL) Databases. Interfaces are frequently standardized and commonly feature a uniform query language and even native DB query mapping. However, Database Portability may be hindered due to non-uniform abstractions. As for mapping strategies, current frameworks do not fully exploit NoSQL's modeling potential, such as (i) the embedding of relationship data within referring objects’ records, (ii) mapping at the individual object-level vs. class-level, and (iii) lacking collection normalization despite being supported for associations or when using relational Databases. Conclusion: The study consolidates knowledge on available ONDM frameworks, and applied object-document, object-graph, and object-column mapping patterns. The study can guide practitioners in framework selection, and pinpoints areas of future development and research in this domain, most notably towards improved support for flexible, NoSQL-aware mapping strategies.status: publishe
Bruce E. Martin - One of the best experts on this subject based on the ideXlab platform.
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The Testbed of Object Relational Products
2015Co-Authors: Bruce E. MartinAbstract:A popular architecture for enterprise applications is one of a stateless object-based server accessing persistent data through Object-Relational mapping software. The reported benefits of using Object-Relational mapping software are increased developer productivity, greater Database Portability and improved runtime performance over hand-written SQL due to caching. In spite of these supposed benefits, many software architects are suspicious of the "black box " nature of O-R mapping software. Discerning how O-R mapping software actually accesses a Database is difficult
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ICDE - Uncovering Database access optimizations in the middle tier with TORPEDO
21st International Conference on Data Engineering (ICDE'05), 2005Co-Authors: Bruce E. MartinAbstract:A popular architecture for enterprise applications is one of a stateless object-based server accessing persistent data through object-relational mapping software. The reported benefits of using object-relational mapping software are increased developer productivity, greater Database Portability and improved runtime performance over hand-written SQL due to caching. In spite of these supposed benefits, many software architects are suspicious of the "black box" nature of O-R mapping software. Discerning how O-R mapping software actually accesses a Database is difficult. The testbed of object relational products for enterprise distributed objects (TORPEDO) is designed to reveal the sophistication of O-R mapping software in accessing Databases in single server and clustered environments. TORPEDO defines a set of realistic application level operations that detect a significant set of Database access optimizations. TORPEDO supports two standard Java APIs for O-R mapping, namely, container managed persistence (CMP 2.0) and Java data objects (JDO). TORPEDO also supports the TopLink and Hibernate APIs. There are dozens of commercial and open-source O-R mapping products supporting these APIs. Results from running TORPEDO on different O-R mapping systems are comparable. We provide sample results from running TORPEDO on popular O-R mapping solutions. We describe why the optimizations TORPEDO reveals are important and how the application level operations detect the optimizations.
Vincent Reniers - One of the best experts on this subject based on the ideXlab platform.
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Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks
Information Systems, 2019Co-Authors: Vincent Reniers, Dimitri Van Landuyt, Ansar Rafique, Wouter JoosenAbstract:Abstract Context: Software applications frequently interact with Database systems to persist and retrieve objects. Object mapping frameworks address (i) the bi-directional conversion of data between object and target Database and (ii) provide a programmatic interface for querying and storing data. The rise of NoSQL Databases poses challenges beyond object-relational mapping (ORM) frameworks to abstract from various data models and non-standardized API’s, but also take into account the different Database capabilities (e.g. unsupported query operators, data ordering). Objective: A systematic survey study of existing Object-NoSQL data mapping (ONDM) frameworks. Specific focus is given to the level of abstraction of data and operations to multiple Database technologies, as a means to limit vendor and technology lock-in and an enabler for multi-store and polyglot architectures. Additional attention is paid to mapping strategies that are specific to NoSQL Databases (e.g. object embedding, schema flexibility). Method: A systematic search methodology identifies all relevant object mapping frameworks (in total 341 frameworks). Subsequently, a subset of ONDM frameworks is selected and systematically compared in terms of criteria of: Database support, interface and query functionality, architecture and software coupling. Secondly, we provide an in-depth comparison of object-oriented mapping strategies for classes, inheritance, relationships, and attribute types to NoSQL data models. Results: ONDM frameworks are most prevalent in Java, Node.JS, Python, and overall 54 frameworks support multiple (NoSQL) Databases. Interfaces are frequently standardized and commonly feature a uniform query language and even native DB query mapping. However, Database Portability may be hindered due to non-uniform abstractions. As for mapping strategies, current frameworks do not fully exploit NoSQL’s modeling potential, such as (i) the embedding of relationship data within referring objects’ records, (ii) mapping at the individual object-level vs. class-level, and (iii) lacking collection normalization despite being supported for associations or when using relational Databases. Conclusion: The study consolidates knowledge on available ONDM frameworks, and applied object-document, object-graph, and object-column mapping patterns. The study can guide practitioners in framework selection, and pinpoints areas of future development and research in this domain, most notably towards improved support for flexible, NoSQL-aware mapping strategies.
Reniers Vincent - One of the best experts on this subject based on the ideXlab platform.
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Object to NoSQL Database Mappers (ONDM): A systematic survey and comparison of frameworks
'Elsevier BV', 2019Co-Authors: Reniers Vincent, Van Landuyt Dimitri, Rafique Ansar, Joosen WouterAbstract:© 2019 Elsevier Ltd Context: Software applications frequently interact with Database systems to persist and retrieve objects. Object mapping frameworks address (i) the bi-directional conversion of data between object and target Database and (ii) provide a programmatic interface for querying and storing data. The rise of NoSQL Databases poses challenges beyond object-relational mapping (ORM) frameworks to abstract from various data models and non-standardized API's, but also take into account the different Database capabilities (e.g. unsupported query operators, data ordering). Objective: A systematic survey study of existing Object-NoSQL data mapping (ONDM) frameworks. Specific focus is given to the level of abstraction of data and operations to multiple Database technologies, as a means to limit vendor and technology lock-in and an enabler for multi-store and polyglot architectures. Additional attention is paid to mapping strategies that are specific to NoSQL Databases (e.g. object embedding, schema flexibility). Method: A systematic search methodology identifies all relevant object mapping frameworks (in total 341 frameworks). Subsequently, a subset of ONDM frameworks is selected and systematically compared in terms of criteria of: Database support, interface and query functionality, architecture and software coupling. Secondly, we provide an in-depth comparison of object-oriented mapping strategies for classes, inheritance, relationships, and attribute types to NoSQL data models. Results: ONDM frameworks are most prevalent in Java, Node.JS, Python, and overall 54 frameworks support multiple (NoSQL) Databases. Interfaces are frequently standardized and commonly feature a uniform query language and even native DB query mapping. However, Database Portability may be hindered due to non-uniform abstractions. As for mapping strategies, current frameworks do not fully exploit NoSQL's modeling potential, such as (i) the embedding of relationship data within referring objects’ records, (ii) mapping at the individual object-level vs. class-level, and (iii) lacking collection normalization despite being supported for associations or when using relational Databases. Conclusion: The study consolidates knowledge on available ONDM frameworks, and applied object-document, object-graph, and object-column mapping patterns. The study can guide practitioners in framework selection, and pinpoints areas of future development and research in this domain, most notably towards improved support for flexible, NoSQL-aware mapping strategies.status: publishe
