Update Propagator for Joint Scalable Storage

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.

[1]  Amit P. Sheth,et al.  Management of interdependent data: specifying dependency and consistency requirements , 1990, [1990] Proceedings. Workshop on the Management of Replicated Data.

[2]  Willy Zwaenepoel,et al.  Performance and scalability of EJB applications , 2002, OOPSLA '02.

[3]  Hamid Pirahesh,et al.  Cache Tables: Paving the Way for an Adaptive Database Cache , 2003, VLDB.

[4]  Patrick Valduriez Principles of Distributed Data Management in 2020? , 2011, DEXA.

[5]  Sriram Padmanabhan,et al.  DBProxy: a dynamic data cache for web applications , 2003, Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405).

[6]  Inderpal Singh Mumick,et al.  Incremental maintenance of aggregate and outerjoin expressions , 2006, Inf. Syst..

[7]  Divyakant Agrawal,et al.  Database Scalability, Elasticity, and Autonomy in the Cloud - (Extended Abstract) , 2011, DASFAA.

[8]  Divyakant Agrawal,et al.  CachePortal II: Acceleration of Very Large Scale Data Center-Hosted Database-driven Web Applications , 2003, VLDB.

[9]  Krzysztof Stencel,et al.  Consistent Caching of Data Objects in Database Driven Websites , 2010, ADBIS.

[10]  Aleksa Vukotic,et al.  Neo4j in Action , 2014 .

[11]  Eric A. Brewer,et al.  Towards robust distributed systems (abstract) , 2000, PODC '00.

[12]  V. S. Subrahmanian,et al.  Maintaining views incrementally , 1993, SIGMOD Conference.

[13]  Wilson C. Hsieh,et al.  Bigtable: A Distributed Storage System for Structured Data , 2006, TOCS.

[14]  Yannis Manolopoulos,et al.  Cache Management for Web-Powered Databases , 2005, Encyclopedia of Information Science and Technology.

[15]  Michael Stonebraker,et al.  "One Size Fits All": An Idea Whose Time Has Come and Gone (Abstract) , 2005, ICDE.

[16]  Divyakant Agrawal,et al.  G-Store: a scalable data store for transactional multi key access in the cloud , 2010, SoCC '10.

[17]  Mahadev Satyanarayanan,et al.  Consistency-preserving caching of dynamic database content , 2007, WWW '07.

[18]  7th Symposium on Operating Systems Design and Implementation (OSDI '06), November 6-8, Seattle, WA, USA , 2006, OSDI.

[19]  Werner Vogels,et al.  Building reliable distributed systems at a worldwide scale demands trade-offs between consistency and availability. , 2022 .

[20]  Nancy A. Lynch,et al.  Brewer's conjecture and the feasibility of consistent, available, partition-tolerant web services , 2002, SIGA.

[21]  Howard Gobioff,et al.  The Google file system , 2003, SOSP '03.

[22]  Kristina Chodorow,et al.  MongoDB - The Definitive Guide: Powerful and Scalable Data Storage , 2019 .

[23]  Hamid Pirahesh,et al.  DBCache: middle-tier database caching for highly scalable e-business architectures , 2003, SIGMOD '03.

[24]  Ethan Cerami,et al.  Web Services Essentials , 2002 .

[25]  Scalable Consistency Management for Web Database Caches , 2006 .

[26]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[27]  J. Davenport Editor , 1960 .

[28]  Carlo Curino,et al.  Relational Cloud: a Database Service for the cloud , 2011, CIDR.

[29]  Reuven M. Lerner At the forge: Redis , 2010 .

[30]  Mark S. Squillante,et al.  Efficiently serving dynamic data at highly accessed web sites , 2004, IEEE/ACM Transactions on Networking.

[31]  Tim Kraska,et al.  Cloudy , 2010, Proc. VLDB Endow..

[32]  Adam Silberstein,et al.  Benchmarking cloud serving systems with YCSB , 2010, SoCC '10.

[33]  Frank Wm. Tompa,et al.  Efficiently updating materialized views , 1986, SIGMOD '86.

[34]  Bruce M. Maggs,et al.  Invalidation Clues for Database Scalability Services , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[35]  Werner Vogels,et al.  Dynamo: amazon's highly available key-value store , 2007, SOSP.

[36]  Michael Burrows,et al.  The Chubby Lock Service for Loosely-Coupled Distributed Systems , 2006, OSDI.

[37]  Raghu Ramakrishnan,et al.  Caching with 'Good Enough' Currency, Consistency, and Completeness , 2005, VLDB.

[38]  Tim Kraska,et al.  An evaluation of alternative architectures for transaction processing in the cloud , 2010, SIGMOD Conference.

[39]  Mohamed F. Mokbel,et al.  Deuteronomy: Transaction Support for Cloud Data , 2011, CIDR.

[40]  Gustavo Alonso,et al.  Consistency Rationing in the Cloud: Pay only when it matters , 2009, Proc. VLDB Endow..

[41]  Michael Stonebraker Proceedings of the 1983 ACM SIGMOD international conference on Management of data , 1983, SIGMOD 1992.

[42]  Prashant Malik,et al.  Cassandra: a decentralized structured storage system , 2010, OPSR.

[43]  Inderpal Singh Mumick,et al.  Maintenance of data cubes and summary tables in a warehouse , 1997, SIGMOD '97.

[44]  J. Chris Anderson,et al.  CouchDB - The Definitive Guide: Time to Relax , 2010 .

[45]  Surajit Chaudhuri,et al.  Proceedings of the 11th ACM Symposium on Cloud Computing , 2010 .

[46]  Roberta Cochrane,et al.  How to roll a join: asynchronous incremental view maintenance , 2000, SIGMOD 2000.

[47]  Otis Gospodnetic,et al.  Lucene in Action (In Action series) , 2004 .

[48]  Divesh Srivastava,et al.  Semantic Data Caching and Replacement , 1996, VLDB.

[49]  Shashank Tiwari,et al.  Professional NoSQL , 2011 .

[50]  Shyam Antony,et al.  Data Management Challenges in Cloud Computing Infrastructures , 2010, DNIS.

[51]  Michael Stonebraker,et al.  The End of an Architectural Era (It's Time for a Complete Rewrite) , 2007, VLDB.

[52]  Michael Stonebraker,et al.  SQL databases v. NoSQL databases , 2010, CACM.

[53]  James R. Anderson James R , 2006 .

[54]  Pat Helland,et al.  Life beyond Distributed Transactions: an Apostate's Opinion , 2007, CIDR.

[55]  Arun Iyengar,et al.  A scalable system for consistently caching dynamic Web data , 1999, IEEE INFOCOM '99. Conference on Computer Communications. Proceedings. Eighteenth Annual Joint Conference of the IEEE Computer and Communications Societies. The Future is Now (Cat. No.99CH36320).

[56]  Chris Wasik Managing Cache Consistency to Scale Dynamic Web Systems , 2007 .

[57]  Bruce M. Maggs,et al.  Scalable query result caching for web applications , 2008, Proc. VLDB Endow..

[58]  Daniel M. Dias,et al.  High-Performance Web Site Design Techniques , 2000, IEEE Internet Comput..

[59]  Surajit Chaudhuri,et al.  Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC 2010, Indianapolis, Indiana, USA, June 10-11, 2010 , 2010, ACM Symposium on Cloud Computing.

[60]  Jeffrey F. Naughton,et al.  Middle-tier database caching for e-business , 2002, SIGMOD '02.

[61]  Beng Chin Ooi,et al.  ES2: A cloud data storage system for supporting both OLTP and OLAP , 2011, 2011 IEEE 27th International Conference on Data Engineering.