Google BigQuery Benchmark — DoIT International :: Helping businesses adopt, manage and enhance cloud solutions from Google and Zendesk
By Vadim Solovey, Google Developer Expert.Recently, I came across an interesting benchmark of BigData systems based on "A Comparison of Approaches to Large-Scale Data Analysis" by Pavlo et al. (SIGMOD 2009). Based on the benchmark methodology, the APMLab guys from Berkeley University developed an open-source software that allows anyone to run this benchmark using public cloud (AWS in this case).Th
Big Data Benchmark
Click Here for the previous version of the benchmark Introduction Several analytic frameworks have been announced in the last year. Among them are inexpensive data-warehousing solutions based on traditional Massively Parallel Processor (MPP) architectures (Redshift), systems which impose MPP-like execution engines on top of Hadoop (Impala, HAWQ), and systems which optimize MapReduce to improve per
Amazon Redshift is 10x faster and cheaper than Hadoop + Hive
2. Amazon Redshift took 155 seconds to run our queries for 1.2TB data Hadoop + Hive took 1491 seconds to run our queries for 1.2TB data Amazon Redshift was 10X faster Amazon Redshift cost $20 to run a query every 30 minutes Hadoop + Hive took $210 to run a query every 30 minutes Amazon Redshift was 10X cost effective www.flydata.com 3. Amazon Redshift is a new data warehouse for big data on the cl
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Amazon Redshift ベンチマーク Hadoop + Hiveと比較
