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authorReynold Xin <rxin@databricks.com>2016-11-15 22:32:03 -0800
committerReynold Xin <rxin@databricks.com>2016-11-15 22:32:03 -0800
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+---
+layout: post
+title: Spark wins CloudSort Benchmark as the most efficient engine
+categories:
+- News
+tags: []
+status: publish
+type: post
+published: true
+meta:
+ _edit_last: '4'
+ _wpas_done_all: '1'
+---
+
+We are proud to announce that Apache Spark won the <a href="http://sortbenchmark.org/">2016 CloudSort Benchmark</a> (both Daytona and Indy category). A joint team from Nanjing University, Alibaba Group, and Databricks Inc. entered the competition using NADSort, a distributed sorting program built on top of Spark, and set a new world record as the most cost-efficient way to sort 100TB of data.
+
+They sorted 100TB of data using only $144 USD worth of public cloud resources, beating the previous record that cost $451 USD by the University of California, San Diego.
+
+This adds to the 2014 GraySort record Spark won, and validates Spark as the most efficient data processing engine.
+
+For more information, see the <a href="https://databricks.com/blog/2016/11/14/setting-new-world-record-apache-spark.html">Databricks blog article (in English)</a> written by Spark committer Reynold Xin, or the Nanjing University <a href="http://scit.nju.edu.cn/Item/1193.aspx">press release (in Chinese)</a>.
+