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alexdebrie.com | ||
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blog.tanelpoder.com
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| | | | | You may remember my previous article about high-performance I/O for cloud databases, where I tested out the Silk Platform and got a single Azure VM to do over 5 GB/s (gigaBytes/s) of I/O for my large database query workload. The magic was in using iSCSI over the switched cloud compute network to multiple "data VMs" at the virtualized storage layer for high I/O throughput and scalability. Well, the Silk folks are at it again and Chris Buckel (@flashdba) just sent me screenshots of similar test runs using the latest Azure "v5" instance as the single large database node and they achieved over 10 GB/s scanning rate for reads and 6 GB/s write rate with large I/Os! - Linux, Oracle, SQL performance tuning and troubleshooting - consulting & training. | |
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timilearning.com
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| | | | | My notes from the second chapter of Martin Kleppmann's book: Designing Data Intensive Applications. | |
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www.ibd.com
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| | | | | Today's article in O'Reilly's Radar by Joseph Hellerstein, is a concise synopsis of the state-of-the-art large scale data analysis. It compares the Enterprise IT dominant Relational Database paradigm to the emerging (with a bullet!) MapReduce / Hadoop technologies. Professor Hellerstein, from UC Berkeley lives this stuff as a leading researcher on databases and distributed systems. | |
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d2iq.com
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| | | The best way to bring cloud and cluster sprawl under control is through centralized multi-cloud and multi-cluster fleet management. | ||
