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"Automated C-Store: Vending's Partner or Competitor?" was the headline of a recent article in the trade journal Automatic Merchandiser.
He created several databases, including C-Store (2005; a database that made use of columns, rather than rows, for improved performance), H-Store (2007; a database that relied on accessing a computer's memory rather than disk storage), and SciDB (2011; an array-based relational database used in machine learning and statistical processing).
C-store is a disk-oriented column-store database.
Let us characterize the research ones briefly: C-store is a disk-oriented column-store database.
This option was described in the original C-Store paper [75] and in the Star Schema Benchmark [76, section 3.1] (multiple sort orders).
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Upland grassland soils are an important terrestrial carbon (C) store and provide vital ecosystem services such as climate regulation.
Therefore increasing efforts have been undertaken to manage CWD as a habitat component and C store in forest ecosystems.
Additional field data are needed, particularly for Papua provinces, to better constrain the estimate of Indonesia's total peat C store.
Indonesia's peat C store is often cited as 57 GtC, the value reported by Page et al. [2] in their assessment of global tropical peat C pools.
Although further work is required to improve estimates of the spatial and temporal distribution of C, our data have demonstrated the substantial C store with the Makgadikgadi environment and the important role of biological crusts in the C cycle.
Southeast Asia contains the largest proportion of tropical peatland with an estimated 41% of tropical peatland area and 65% of the tropical peat C store (105 GtC) [2, 3].
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