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Datalution: a tool for continuous schema evolution in NoSQL-backed web applications

Published: 21 July 2016 Publication History

Abstract

When an incremental release of a web application is deployed, the structure of data already persisted in the production database may no longer match what the application code expects. Traditionally, eager schema migration is called for, where all legacy data is migrated in one go. With the growing popularity of schema-flexible NoSQL data stores, lazy forms of data migration have emerged: Legacy entities are migrated on-the-fly, one at-a-time, when they are loaded by the application. In this demo, we present Datalution, a tool demonstrating the merits of lazy data migration. Datalution can apply chains of pending schema changes, due to its Datalog-based internal representation. The Datalution approach thus ensures that schema evolution, as part of continous deployment, is carried out correctly.

References

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Curino, C., Moon, H. J., Tanca, L., and Zaniolo, C. Schema Evolution in Wikipedia - Toward a Web Information System Benchmark. In ICEIS’08 (2008).
[2]
Saur, K., Dumitras, T., and Hicks, M. W. Evolving NoSQL Databases Without Downtime. CoRR abs/1506.08800 (2015). Technical report.
[3]
Scherzinger, S., Störl, U., and Klettke, M. Managing Schema Evolution in NoSQL Data Stores. In Proceedings DBPL’13 (2013).
[4]
Scherzinger, S., Störl, U., and Klettke, M. A Datalog-based Protocol for Lazy Data Migration in Agile NoSQL Application Development. In Proceedings DBPL’15 (2015).
[5]
Wiech, K., Sombach, S., and Scherzinger, S. A Datalog-based Tool for Schema Evolution in NoSQL Databases. Poster presentation at XP’16, 2016.

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cover image ACM Conferences
QUDOS 2016: Proceedings of the 2nd International Workshop on Quality-Aware DevOps
July 2016
47 pages
ISBN:9781450344111
DOI:10.1145/2945408
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 July 2016

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Author Tags

  1. NoSQL data stores
  2. Schema evolution
  3. Software evolution

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