A Classification of Object-Relational Impedance Mismatch

Ireland, Christopher; Bowers, David; Newton, Michael A.; Waugh, Kevin

doi:10.1109/dbkda.2009.11

Cited by 64 publications

(43 citation statements)

References 6 publications

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“…However, in practice, the OODM is adapted and implemented into relational or object-relational database management systems with spatial capabilities, and database managers have to deal with incompatibilities at the conceptual level. This is a case of the object-relational impedance mismatch, and has been clearly identified in literature as a problem of data structure due to paradigm differences [4]. An example of LU/LC classification of a single parcel is shown in Fig.…”

Section: Land Use and Land Cover Databases In The Eumentioning

confidence: 99%

Should EU land use and land cover data be managed with a NOSQL document store?

Navarro-Carrión¹,

Zaragozí²,

Ramon-Morte³

et al. 2016

Int. J. DNE

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Land cover (LC) is a scientific landscape classification based on physical properties of earth materials. This information is usually retrieved through remote sensing techniques (e.g. forest cover, urban, clay content, among others). In contrast, Land use (LU) is defined from an anthropocentric point of view. It describes how a specific area is used (e.g. it is usual to indicate whether a territory supports an intensive, extensive use or it is unused). Both geospatial layers are essential inputs in many socio-economic and environmental studies. The INSPIRE directive provides technical data specifications for harmonization and sharing of voluminous LU/ LC datasets across all countries of the EU. The INSPIRE initiative proposes Object-Oriented Modelling as a data modelling methodology. However, the most used Geographic Information Systems (GIS) are built upon relational databases. This may jeopardize LU/LC data usability, since GIS practitioners will eventually face the object-relational impedance mismatch. In this paper, the authors introduce the SIOSE database (Spanish Land Cover and Land Use Information System), which was the first implementation of an object-oriented land cover and Land-use datamodel, in line with the recommendation of the INSPIRE Directive, separating both themes. SIOSE data can be downloaded as relational database files, where information describing each single LU/LC object is divided among several related tables, so database queries can be complex and time consuming. The authors show these technical complexities through a computational experience, comparing SQL and NoSQL databases for querying spatial data downloaded from SIOSE. Finally, the authors conclude that NoSQL geodatabases deserve to be further explored because they could scale for LU/LC data, both horizontally and vertically, better than relational geodatabases, improving usability and making the most of the EU harmonization efforts. Keywords: Land Use, Land Cover, document store, SIOSE, geodatabase, PostgreSQL, jsonb LAND USE AND LAND COVER DATABASES IN THE EULand is a limited resource and its mismanagement is one of the main drivers of global change, with significant effects on ecosystem functions, goods and services [1]. There are complex environmental problems such as the over-exploitation of natural resources, biodiversity loss or climate change that require a long-term management perspective of natural resources. Many studies agree that these problems can be aggravated by land-use changes, so it is mandatory to monitor and apply long-term management policies at different scales [2].Land use (LU) and land cover (LC) information at national and regional level has been historically recorded in many EU Member States because of their environmental and territorial management's needs and requirements. In addition to Corine Land Cover (CLC) 1990 databases, many EU countries have been producing LC databases to manage and satisfy their requirements on environmental, agricultural, forest and land planning issues. As a conse...

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Section: Land Use and Land Cover Databases In The Eumentioning

confidence: 99%

Should EU land use and land cover data be managed with a NOSQL document store?

Navarro-Carrión¹,

Zaragozí²,

Ramon-Morte³

et al. 2016

Int. J. DNE

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“…In the context of Object-Relational Mappers (ORMs), this problem is commonly referred to as the objectrelational impedance mismatch [32], and one may argue that in a NoSQL context, such mismatch problems may be more significant due to the technological heterogeneity among NoSQL systems and the wide range of features and data models supported in NoSQL.…”

Section: Jpa-nosql Interface Mismatchmentioning

confidence: 99%

Object-NoSQL Database Mappers: a benchmark study on the performance overhead

Reniers

Rafique

Landuyt

et al. 2017

J Internet Serv Appl

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In recent years, the hegemony of traditional relational database management systems (RDBMSs) has declined in favour of non-relational databases (NoSQL). These database technologies are better adapted to meet the requirements of large-scale (web) infrastructures handling Big Data by providing elastic and horizontal scalability. Each NoSQL technology however is suited for specific use cases and data models. As a consequence, NoSQL adopters are faced with tremendous heterogeneity in terms of data models, database capabilities and application programming interfaces (APIs). Opting for a specific NoSQL database poses the immediate problem of vendor or technology lock-in. A solution has been proposed in the shape of Object-NoSQL Database Mappers (ONDMs), which provide a uniform abstraction interface for different NoSQL technologies. Such ONDMs however come at a cost of increased performance overhead, which may have a significant economic impact, especially in large distributed setups involving massive volumes of data. In this paper, we present a benchmark study quantifying and comparing the performance overhead introduced by Object-NoSQL Database Mappers, for create, read, update and search operations. Our benchmarks involve five of the most promising and industry-ready ONDMs: Impetus Kundera, Apache Gora, EclipseLink, DataNucleus and Hibernate OGM, and are executed both on a single node and a 9-node cluster setup. Our main findings are summarised as follows: (i) the introduced overhead is substantial for database operations in-memory, however on-disk operations and high network latency result in a negligible overhead, (ii) we found fundamental mismatches between standardised ONDM APIs and the technical capabilities of the NoSQL database, (iii) search performance overhead increases linearly with the number of results, (iv) DataNucleus and Hibernate OGM's search overhead is exceptionally high in comparison to the other ONDMs.

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“…in [5,15,16,2]. Among others, Fowler provides in his book [1] a wide collection of patterns to common object relational mapping problems.…”

Section: Related Workmentioning

confidence: 99%

Declarative Representation of Programming Access to Ontologies

Scheglmann

Scherp

Staab

2012

Lecture Notes in Computer Science

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Abstract. Using ontologies in software applications is a challenging task due to the chasm between the logics-based world of ontologies and the object-oriented world of software applications. The logics-based representation emphasizes the meaning of concepts and properties, i.e., their semantics. The modeler in the object-oriented paradigm also takes into account the pragmatics, i.e., how the classes are used, by whom, and why. To enable a comprehensive use of logics-based representations in objectoriented software systems, a seamless integration of the two paradigms is needed. However, the pragmatic issues of using logic-based knowledge in object-oriented software applications has yet not been considered sufficiently. Rather, the pragmatic issues that arise in using an ontology, e.g., which classes to instantiate in which order, remains a task to be carefully considered by the application developer. In this paper, we present a declarative representation for designing and applying programming access to ontologies. Based on this declarative representation, we have build OntoMDE, a model-driven engineering toolkit that we have applied to several example ontologies with different Characteristics.

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A Classification of Object-Relational Impedance Mismatch

Cited by 64 publications

References 6 publications

Should EU land use and land cover data be managed with a NOSQL document store?

Should EU land use and land cover data be managed with a NOSQL document store?

Object-NoSQL Database Mappers: a benchmark study on the performance overhead

Declarative Representation of Programming Access to Ontologies

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