tag:blogger.com,1999:blog-3346090548501966296.post6454308653952217481..comments2024-03-26T05:03:04.875-07:00Comments on Perspectives on LedgerSMB: PostgreSQL vs HadoopChris Travershttp://www.blogger.com/profile/06211762965865744803noreply@blogger.comBlogger8125tag:blogger.com,1999:blog-3346090548501966296.post-46873819473273326272024-01-24T23:13:13.493-08:002024-01-24T23:13:13.493-08:00clear-american-sparkling-water In conclusion, Clea...<a href="https://healthylifehuman.com/clear-american-sparkling-water/" rel="nofollow">clear-american-sparkling-water</a> In conclusion, Clear American Sparkling Water has emerged as a clear favorite in the competitive beverage landscape. Its crisp effervescence, diverse flavor offerings, health-conscious attributes, and commitment to sustainability make it a compelling choice for those who seek more from their refreshment. 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You're correct that if your data doesn't shard well you're still in trouble. Though, doesn't the same apply to hadoop? Or does it just use a hash of the entire row/document to partition?mehttps://www.blogger.com/profile/04742962706293447175noreply@blogger.comtag:blogger.com,1999:blog-3346090548501966296.post-76269976737790663162016-08-20T00:54:27.699-07:002016-08-20T00:54:27.699-07:00But one point worth noting is that "big data&...But one point worth noting is that "big data" is a bit of a buzzword and poorly defined topic. Columnar stores help certain kinds of aggregation. Index oriented tables help one tune certain kinds of access patterns. Those are important tools in dealing with data volume problems.<br /><br />But one of the things which has really been difficult in the deployment I work with that is moving to Hadoop is the fact that TOAST performance overhead is rather difficult to measure and in order to get adequate performance, certain things have had to move to non-1NF designs. Even when you are dealing with structured data, there are access pattern corners where one has to be rather imaginative to keep performance up.<br /><br />So it is a mistake to think that all volume problems are the same, or all velocity problems are the same. Once you get into TB of data, attention to detail and awareness of your specific issues become important.<br /><br />Today PostgreSQL can deal well with certain kinds of big data problems. And those are expanding. But we should be careful not to be like the folks who think Hadoop is the answer to everything ;-)Chris Travershttps://www.blogger.com/profile/06211762965865744803noreply@blogger.comtag:blogger.com,1999:blog-3346090548501966296.post-31946591107394025622016-08-20T00:44:42.664-07:002016-08-20T00:44:42.664-07:00Certainly for some kinds of big data. And anythin...Certainly for some kinds of big data. And anything that helps certain areas do better is a major win. Having index-oriented tables would also help with certain volume-related issues as well (and there has been talk about that for some time).Chris Travershttps://www.blogger.com/profile/06211762965865744803noreply@blogger.comtag:blogger.com,1999:blog-3346090548501966296.post-85708269095830775362016-08-19T20:00:22.339-07:002016-08-19T20:00:22.339-07:00PostgreSQL 10 roadmap from 2ndQuadrant on columnar...PostgreSQL 10 roadmap from 2ndQuadrant on columnar indexes may make PostgreSQL suitable for big data:<br />http://blog.2ndquadrant.com/postgresql-10-roadmap/yoonghmhttps://www.blogger.com/profile/05817590043333850082noreply@blogger.com