C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Optimizing bitmap indices with efficient compression
ACM Transactions on Database Systems (TODS)
Integrating compression and execution in column-oriented database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Graceful database schema evolution: the PRISM workbench
Proceedings of the VLDB Endowment
Managing and querying transaction-time databases under schema evolution
Proceedings of the VLDB Endowment
Efficient and scalable data evolution with column oriented databases
Proceedings of the 14th International Conference on Extending Database Technology
Minimal data sets vs. synchronized data copies in a schema and data versioning system
Proceedings of the 4th workshop on Workshop for Ph.D. students in information & knowledge management
Static analysis of XML document adaptations
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
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Database evolution is the process of updating the schema of a database or data warehouse (schema evolution) and evolving the data to the updated schema (data evolution). Database evolution is often necessitated in relational databases due to the changes of data or workload, the suboptimal initial schema design, or the availability of new knowledge of the database. It involves two steps: updating the database schema, and evolving the data to the new schema. Despite the capability of commercial RDBMSs to well optimize query processing, evolving the data during a database evolution through SQL queries is shown to be prohibitively costly. We designed and developed CODS, a platform for efficient data level data evolution in column oriented databases, which evolves the data to the new schema without materializing query results or unnecessary compression/decompression as occurred in traditional query level approaches. CODS ameliorates the efficiency of data evolution by orders of magnitude compared with commercial or open source RDBMSs.