- MonetDB/DataCell: online analytics in a streaming column-store
- Proceedings of the VLDB Endowment
- Volume | Issue number
- 5 | 12
- Pages (from-to)
- Document type
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
In DataCell, we design streaming functionalities in a modern relational database kernel which targets big data analytics. This includes exploitation of both its storage/execution engine and its optimizer infrastructure. We investigate the opportunities and challenges that arise with such a direction
and we show that it carries signiﬁcant advantages for modern applications in need for online analytics such as web logs, network monitoring and scientiﬁc data management.
The major challenge then becomes the eﬃcient support for specialized stream features, e.g., multi-query processing and incremental window-based processing as well as exploiting standard DBMS functionalities in a streaming environment such as indexing. This demo presents DataCell, an extension of the MonetDB open-source column-store for online analytics. The demo gives users the opportunity to experience the features of DataCell such as processing both stream and persistent
data and performing window based processing. The demo provides a visual interface to monitor the critical system components, e.g., how query plans transform from typical DBMS query plans to online query plans, how data ﬂows through the query plans as the streams evolve, how DataCell maintains intermediate results in columnar form to avoid repeated evaluation of the same stream portions, etc.
The demo also provides the ability to interactively set the test scenarios and various DataCell knobs.
- Proceedings title: Proceedings of the 38th International Conference on Very Large Data Bases, Istanbul, Turkey
Editors: Z. Meral Özsoyoğlu
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