MADIS: A Slim Middleware for Database Replication

• Published in: Euro-Par 2005 Parallel Processing pp. 349 - 359
• Main Authors: Irún-Briz, Luis, Decker, Hendrik, de Juan-Marín, Rubén, Castro-Company, Francisco, Armendáriz-Iñigo, Jose E., Muñoz-Escoí, Francesc D.
• Format: Book Chapter Conference Proceeding
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2005; Springer
• Series: Lecture Notes in Computer Science
• Subjects: Applied sciences; Computer science; control theory; systems; Computer systems and distributed systems. User interface; Database Schema; Exact sciences and technology; Java Implementation; Original Schema; Query Execution; Software; User Application; Availability; Performance evaluation; High performance; Replicated databases; Database; Metadata; Replication; Distributed system; Distributed computing; Middleware
• ISBN: 3540287000; 9783540287001
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/11549468_41

Data replication serves to improve the availability and performance of distributed systems. The price to be paid consists of costs caused by protocols by which a sufficient degree of consistency of replicated data is maintained. Different kinds of targeted applications require different kinds of replication protocols, each one requiring a different set of metadata. We discuss the middleware architecture used in the MADIS project for maintaining the consistency of replicated databases. Instead of reinventing wheels, MADIS makes use of basic resources provided by conventional database systems (e.g. triggers, views, etc) to achieve its purpose, to a large extent. So, the underlying databases can perform more efficiently many of the routines needed to support any consistency protocol, the implementation of which thus becomes much simpler and easier. MADIS enables the databases to simultaneously maintain different metadata needed for different replication protocols, so that the latter can be chosen, plugged in and exchanged on the fly as online-configurable modules, in order to fit the shifting needs of given applications best, at each moment.