Defining Referential Integrity Constraints in Graph-oriented Datastores

2020 ◽  
Author(s):  
Thibaud Masson ◽  
Romain Ravet ◽  
Francisco Ruiz ◽  
Souhaila Serbout ◽  
Diego Ruiz ◽  
...  
Keyword(s):  
Integrity Constraints ◽  
Referential Integrity

scholarly journals Integrity Constraint Checking in Distributed Nested Transactions over a Database Cluster

2006 ◽  
Vol 9 (2) ◽  
Author(s):  
Stephane Gançarski ◽  
Claudia León ◽  
Hubert Naacke ◽  
Marta Rukoz ◽  
Pablo Santini
Keyword(s):  
Distributed Systems ◽  
Database System ◽  
Integrity Constraints ◽  
Global Constraints ◽  
Integrity Constraint ◽  
Nested Transactions ◽  
Pc Cluster ◽  
Constraint Checking ◽  
Database Cluster ◽  
Referential Integrity

This paper presents a solution to check referential integrity constraints and conjunctive global constraints in a relational multi database system. It also presents the experimental results obtained by implementing this solution over a PC cluster with Oracle9i DBMS. The goal of those experimentations is to measure the time spent to check global constraints in a distributed systems. The results show that the overhead induced by our distributed constraint checking is reduced by 50% compared to a centralized checking of constraints.

scholarly journals A design specification and a server implementation of the inverse referential integrity constraints

2013 ◽  
Vol 10 (1) ◽  
pp. 283-320 ◽  
Author(s):  
Slavica Aleksic ◽  
Sonja Ristic ◽  
Ivan Lukovic ◽  
Milan Celikovic
Keyword(s):  
Relational Database ◽  
Database Management ◽  
Database Management Systems ◽  
Integrity Constraints ◽  
Management Systems ◽  
Design Specification ◽  
Referential Integrity ◽  
Relational Database Management ◽  
Relational Database Management Systems

The inverse referential integrity constraints (IRICs) are specialization of non-key-based inclusion dependencies (INDs). Keybased INDs (referential integrity constraints) may be fully enforced by most current relational database management systems (RDBMSs). On the contrary, non-key-based INDs are completely disregarded by actual RDBMSs, obliging the users to manage them via custom procedures and/or triggers. In this paper we present an approach to the automated implementation of IRICs integrated in the SQL Generator tool that we developed as a part of the IIS

scholarly journals Referential Integrity in  Cloud NoSQL Databases

2021 ◽  
Author(s):  
◽  
Harsha Raja
Keyword(s):  
Application Programming Interface ◽  
Middle Layer ◽  
Integrity Constraints ◽  
Nosql Databases ◽  
Computing Services ◽  
Trade Offs ◽  
Database As A Service ◽  
Application Programming ◽  
Referential Integrity ◽  
Programming Interface

<p>Cloud computing delivers on-demand access to essential computing services providing benefits such as reduced maintenance, lower costs, global access, and others. One of its important and prominent services is Database as a Service (DaaS) which includes cloud Database Management Systems (DBMSs). Cloud DBMSs commonly adopt the key-value data model and are called Not only SQL (NoSQL) DBMSs. These provide cloud suitable features like scalability, flexibility and robustness, but in order to provide these, features such as referential integrity are often sacrificed. In such cases, referential integrity is left to be dealt with by the applications instead of being handled by the cloud DBMSs. Thus, applications are required to either deal with inconsistency in the data (e.g. dangling references) or to incorporate the necessary logic to ensure that referential integrity is maintained. This thesis presents an Application Programming Interface (API) that serves as a middle layer between the applications and the cloud DBMS in order to maintain referential integrity. The API provides the necessary Create, Read, Update and Delete (CRUD) operations to be performed on the DBMS while ensuring that the referential integrity constraints are satisfied. These constraints are represented as metadata and four different approaches are provided to store it. Furthermore, the performance of these approaches is measured with different referential integrity constraints and evaluated upon a set of experiments in Apache Cassandra, a prominent cloud NoSQL DBMS. The results showed significant differences between the approaches in terms of performance. However, the final word on which one is better depends on the application demands as each approach presents different trade-offs.</p>

scholarly journals Referential Integrity in  Cloud NoSQL Databases

2021 ◽  
Author(s):  
◽  
Harsha Raja
Keyword(s):  
Application Programming Interface ◽  
Middle Layer ◽  
Integrity Constraints ◽  
Nosql Databases ◽  
Computing Services ◽  
Trade Offs ◽  
Database As A Service ◽  
Application Programming ◽  
Referential Integrity ◽  
Programming Interface

<p>Cloud computing delivers on-demand access to essential computing services providing benefits such as reduced maintenance, lower costs, global access, and others. One of its important and prominent services is Database as a Service (DaaS) which includes cloud Database Management Systems (DBMSs). Cloud DBMSs commonly adopt the key-value data model and are called Not only SQL (NoSQL) DBMSs. These provide cloud suitable features like scalability, flexibility and robustness, but in order to provide these, features such as referential integrity are often sacrificed. In such cases, referential integrity is left to be dealt with by the applications instead of being handled by the cloud DBMSs. Thus, applications are required to either deal with inconsistency in the data (e.g. dangling references) or to incorporate the necessary logic to ensure that referential integrity is maintained. This thesis presents an Application Programming Interface (API) that serves as a middle layer between the applications and the cloud DBMS in order to maintain referential integrity. The API provides the necessary Create, Read, Update and Delete (CRUD) operations to be performed on the DBMS while ensuring that the referential integrity constraints are satisfied. These constraints are represented as metadata and four different approaches are provided to store it. Furthermore, the performance of these approaches is measured with different referential integrity constraints and evaluated upon a set of experiments in Apache Cassandra, a prominent cloud NoSQL DBMS. The results showed significant differences between the approaches in terms of performance. However, the final word on which one is better depends on the application demands as each approach presents different trade-offs.</p>

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