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• W4294904080 abstract "Today's Hybrid Transactional and Analytical Processing (HTAP) systems, tackle the ever-growing data in combination with a mixture of transactional and analytical workloads. While optimizing for aspects such as data freshness and performance isolation, they build on the traditional data-to-code principle and may trigger massive cold data transfers that impair the overall performance and scalability. Firstly, in this paper we show that Near-Data Processing (NDP) naturally fits in the HTAP design space. Secondly, we propose an NDP database architecture, allowing transactionally consistent in-situ executions of analytical operations in HTAP settings. We evaluate the proposed architecture in state-of-the-art key/value-stores and multi-versioned DBMS. In contrast to traditional setups, our approach yields robust, resource- and cost-efficient performance." @default.
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• W4294904080 date "2022-06-01" @default.
• W4294904080 modified "2023-09-30" @default.
• W4294904080 title "Near-data processing in database systems on native computational storage under HTAP workloads" @default.
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• W4294904080 doi "https://doi.org/10.14778/3547305.3547307" @default.
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