583 research outputs found

    Secure Transaction Model for NoSQL Database Systems: Review

    Get PDF
    NoSQL cloud database frameworks would consist new sorts of databases that would construct over many cloud hubs and would be skilled about storing and transforming enormous information. NoSQL frameworks need to be progressively utilized within substantial scale provisions that require helter skelter accessibility. What’s more effectiveness for weaker consistency? Consequently, such frameworks need help for standard transactions which give acceptable and stronger consistency. This task proposes another multi-key transactional model which gives NoSQL frameworks standard for transaction backing and stronger level from claiming information consistency. Those methodology is to supplement present NoSQL structural engineering with an additional layer that manages transactions. The recommended model may be configurable the place consistency, accessibility Furthermore effectiveness might make balanced In view of requisition prerequisites. The recommended model may be approved through a model framework utilizing MongoDB. Preliminary examinations show that it ensures stronger consistency Furthermore supports great execution

    Database Middleware for High Performance Transaction Processing with Isolation

    Get PDF
    制度:新 ; 報告番号:甲3289号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/25 ; 早大学位記番号:新559

    Middleware-based Database Replication: The Gaps between Theory and Practice

    Get PDF
    The need for high availability and performance in data management systems has been fueling a long running interest in database replication from both academia and industry. However, academic groups often attack replication problems in isolation, overlooking the need for completeness in their solutions, while commercial teams take a holistic approach that often misses opportunities for fundamental innovation. This has created over time a gap between academic research and industrial practice. This paper aims to characterize the gap along three axes: performance, availability, and administration. We build on our own experience developing and deploying replication systems in commercial and academic settings, as well as on a large body of prior related work. We sift through representative examples from the last decade of open-source, academic, and commercial database replication systems and combine this material with case studies from real systems deployed at Fortune 500 customers. We propose two agendas, one for academic research and one for industrial R&D, which we believe can bridge the gap within 5-10 years. This way, we hope to both motivate and help researchers in making the theory and practice of middleware-based database replication more relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on Management of Data, Vancouver, Canada, June 200

    Transaction management across data stores

    Get PDF
    Companies have evolved from a world where they only had SQL databases to a world where they use different kinds of data stores, such as key­value data stores, document­oriented data stores and graph databases. The reason why they have started to introduce this diversity of persistency models is because different NoSQL technologies bring different data models with associated query languages and/or APIs. However, they are confronted now with a problem in which they have the data scattered across different data stores. This problem lies in that when a business action requires to update the data, the data reside in different data stores, and they are subject to inconsistencies in the event of failure and/or concurrent access. These inconsistencies appear due to the lack of transactional consistency that was guaranteed in traditional SQL databases but is not guaranteed either within the NoSQL data stores or across data stores and databases. CoherentPaaS comes to remedy this need. CoherentPaaS provides an ultra­scalable transactional management layer that can be integrated with any data store with multi­ versioning capabilities. The layer has been integrated with six different data stores, three NoSQL data stores and three SQL­like databases. In this paper, we describe this generic ultra­scalable transactional management layer and focus on its API and how it can be integrated in different ways with different data stores and databases
    corecore