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Performance Analysis of .NET Based Object–Relational Mapping Frameworks

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Beyond Databases, Architectures, and Structures (BDAS 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 424))

Abstract

Object-relational mapping is a technology that connects relationships with object-oriented entities, which aims to eliminate duplicate layers together with costs of maintenance and any errors arising from their existence. A lot of tools and technologies were designed in order to support and implement idea of object-relational mapping. In this paper we present the performance comparison of two most common object-relational mapping interfaces for .NET framework: Entity Framework and NHibernate. In the .NET developers community, there is a lot of discussion today about the similarities and differences of the both technologies. To address this issue, we compared the features and performance of both tools. We analysed the performance of Entity Framework and NHibernate for two different databases (MS SQL Server and PostgreSQL), different query languages (lambda expressions and LINQ for Entity Framework and HQL and Critera API for NHibernate) and compared the results with the standard SqlClient queries. The results show that there is no significant difference between these both tools and we proved that common opinion that NHibernate performs better than Entity Framework is incorrect.

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References

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Correspondence to Aleksandra Gruca .

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© 2014 Springer International Publishing Switzerland

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Gruca, A., Podsiadło, P. (2014). Performance Analysis of .NET Based Object–Relational Mapping Frameworks. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures, and Structures. BDAS 2014. Communications in Computer and Information Science, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-06932-6_5

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  • DOI: https://doi.org/10.1007/978-3-319-06932-6_5

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-06931-9

  • Online ISBN: 978-3-319-06932-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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