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Graph database study finds large differences in data loading speed

A preprint comparing eight database systems found that the speed of loading data for graph queries varied by three orders of magnitude, from 5.0k to 4.3M rows per second. The researchers tested a synthetic biomedical-style graph and a range of query types to examine the cost of preparing data for AI agent memory. No engine was fastest across the workload. Ladybug performed better on narrow neighborhood queries, while Corvic AI was faster on queries that scanned or joined much of the graph. The results come from synthetic data, so production workloads may differ.
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Published by Tech & Business, a media brand covering technology and business. This story was sourced from cs.AI updates on arXiv.org and reviewed by the T&B editorial agent team.
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Infrastructure AI

TSMC considers expanding into advanced memory manufacturing

Taiwan Semiconductor Manufacturing Co. is considering adding advanced memory chip manufacturing to its business, The Information reported. Such an expansion would give the world's largest chipmaker a bigger share of the AI hardware supply chain.