Database Replication Prototype

2002

This paper explores the architecture, implementation and performance of a wide and local area database replication system. The architecture provides peer replication, supporting diverse application semantics, based on a group communication paradigm. Network partitions and merges, computer crashes and recoveries, and message omissions are all handled. Using a generic replication engine and the Spread group communication toolkit, we provide replication

ISPRS International Journal of Geo-Information, 2020

This paper is focused on comparing database replication over spatial data in PostgreSQL and MySQL. Database replication means solving various problems with overloading a single database server with writing and reading queries. There are many replication mechanisms that are able to handle data differently. Criteria for objective comparisons were set for testing and determining the bottleneck of the replication process. The tests were done over the real national vector spatial datasets, namely, ArcCR500, Data200, Natural Earth and Estimated Pedologic-Ecological Unit. HWMonitor Pro was used to monitor the PostgreSQL database, network and system load. Monyog was used to monitor the MySQL activity (data and SQL queries) in real-time. Both database servers were run on computers with the Microsoft Windows operating system. The results from the provided tests of both replication mechanisms led to a better understanding of these mechanisms and allowed informed decisions for future deployment. Graphs and tables include the statistical data and describe the replication mechanisms in specific situations. PostgreSQL with the Slony extension with asynchronous replication synchronized a batch of changes with a high transfer speed and high server load. MySQL with synchronous replication synchronized every change record with low impact on server performance and network bandwidth.

Proceedings 20th IEEE International Conference on Distributed Computing Systems, 2000

Replication is an area of interest to both distributed systems and databases. The solutions developed from these two perspectives are conceptually similar but differ in many aspects: model, assumptions, mechanisms, guarantees provided, and implementation. In this paper, we provide an abstract and "neutral" framework to compare replication techniques from both communities in spite of the many subtle differences. The framework has been designed to emphasize the role played by different mechanisms and to facilitate comparisons. With this, it is possible to get a functional comparison of many ideas that is valuable for both didactic and practical purposes. The paper describes the replication techniques used in both communities, compares them, and points out ways in which they can be integrated to arrive to better, more robust replication protocols.

2011

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

International Journal of Cyber and IT Service Management, 2022

Today's computer applications have ever-increasing database system capabilities and performance. The growing amount of data that has to be processed in a business company makes centralized data processing ineffective. This inefficiency shows itself as a long reaction time. This is in direct opposition to the purpose of utilizing databases in data processing, which is to reduce the amount of time it takes to process data. Another database design is required to tackle this problem. Distributed database technology refers to an architecture in which several servers are linked together, and each one may process and fulfill local queries. Each participating server is responsible for serving one or more requests. In a multi-master replication scenario, all sites are main sites, and all main sites communicate with one another. The distributed database system comprises numerous linked computers that work together as a single system.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

Proceedings of the 2009 EDBT/ICDT Workshops on - EDBT/ICDT '09, 2009

In distributed systems, replication is used for ensuring availability and increasing performances. However, the heavy workload of distributed systems such as web2.0 applications or Global Distribution Systems, limits the benefit of replication if its degree (i.e., the number of replicas) is not controlled. Since every replica must perform all updates eventually, there is a point beyond which adding more replicas does not increase the throughput, because every replica is saturated by applying updates. Moreover, if the replication degree exceeds the optimal threshold, the useless replica would generate an overhead due to extra communication messages. In this paper, we propose a suitable replication management solution in order to reduce useless replicas. To this end, we define two mathematical models which approximate the appropriate number of replicas to achieve a given level of performance. Moreover, we demonstrate the feasibility of our replication management model through simulation. The results expose the effectiveness of our models and their accuracy.

2005

Abstract Data replication is a key technology in distributed systems that enables higher availability and performance. This article surveys optimistic replication algorithms. They allow replica contents to diverge in the short term to support concurrent work practices and tolerate failures in low-quality communication links. The importance of such techniques is increasing as collaboration through wide-area and mobile networks becomes popular.

International Journal of Modern Education and Computer Science, 2013

In this paper, the detailed overview of the database replication is presented. Thereafter, PDDRA (Pre-fetching based dynamic data replication algorithm) algorithm as recently published is detailed. In this algorithm, further, modifications are suggested to minimize the delay in data replication. Finally a mathematical framework is presented to evaluate mean waiting time before a data can be replicated on the requested site.

2008

Database replication has been researched as a solution to overcome the problems of performance and availability of distributed systems. Full database replication, based on group communication systems, is an attempt to enhance performance that works well for a reduced number of sites. If application locality is taken into consideration, partial replication, i.e. not all sites store the full database, also enhances scalability. On the other hand, it is needed to keep all copies consistent. If each DBMS provides SI, the execution of transactions has to be coordinated so as to obtain Generalized-SI (GSI). In this paper, a partial replication protocol providing GSI is introduced that gives a consistent view of the database, providing an adaptive replication technique and supporting the failure and recovery of replicas.