Proceedings of the 1986 ACM SIGMOD international conference on Management of data
SIGMOD86 Conference on Management of Data
Maintenance of data cubes and summary tables in a warehouse
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
How to roll a join: asynchronous incremental view maintenance
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Towards robust distributed systems (abstract)
Proceedings of the nineteenth annual ACM symposium on Principles of distributed computing
High-Performance Web Site Design Techniques
IEEE Internet Computing
Efficiently serving dynamic data at highly accessed web sites
IEEE/ACM Transactions on Networking (TON)
Scalable query result caching for web applications
Proceedings of the VLDB Endowment
Cloudy: a modular cloud storage system
Proceedings of the VLDB Endowment
Principles of distributed data management in 2020?
DEXA'11 Proceedings of the 22nd international conference on Database and expert systems applications - Volume Part I
Data management challenges in cloud computing infrastructures
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
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In recent years, the scalability of web applications has become critical. Web sites get more dynamic and customized. This increases servers' workload. Furthermore, the future increase of load is difficult to predict. Thus, the industry seeks for solutions that scale well. With current technology, almost all items of system architectures can be multiplied when necessary. There are, however, problems with databases in this respect. The traditional approach with a single relational database has become insufficient. In order to achieve scalability, architects add a number of different kinds of storage facilities. This could be error prone because of inconsistencies in stored data. In this paper we present a novel method to assemble systems with multiple storages. We propose an algorithm for update propagation among different storages like multi-column, key-value, and relational databases.