Extracting deltas from column oriented NoSQL databases for different incremental applications and diverse data targets
This paper describes the Change Data Capture (CDC) problems in the context of column-oriented NoSQL databases (CoNoSQLDBs). CDC is a term mostly used by ETL tools and data warehousing environments (DW) to depict a data processing of extracting data changes made at the data sources. Based on analyzin...
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| Vydané v: | Data & knowledge engineering Ročník 93; s. 42 - 59 |
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| Hlavní autori: | , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Elsevier B.V
01.09.2014
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| Predmet: | |
| ISSN: | 0169-023X, 1872-6933 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | This paper describes the Change Data Capture (CDC) problems in the context of column-oriented NoSQL databases (CoNoSQLDBs). CDC is a term mostly used by ETL tools and data warehousing environments (DW) to depict a data processing of extracting data changes made at the data sources. Based on analyzing the impacts and constraints caused by the core features of CoNoSQLDBs, we propose a logical change data (delta) model and the corresponding delta representations which could work with different incremental applications and diverse data targets. Moreover, we present five feasible CDC approaches, i.e. Timestamp-based approach, Audit-column approach, Log-based approach, Trigger-based approach and Snapshot differential approach and indicate the performance winners under different circumstances. |
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| ISSN: | 0169-023X 1872-6933 |
| DOI: | 10.1016/j.datak.2014.07.002 |