The three leaders of the relational database market are responding to the sudden mania for the data processing technology Hadoop in three very different ways.
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"We'd never bring Hadoop code into one of our products," said Microsoft technical fellow and University of Wisconsin-Madison professor David J. DeWitt.
DeWitt's lack of interest is not surprising. DeWitt is an academic expert in parallel SQL databases, having co-invented three of them. He co-authored a paper this spring that argued that SQL databases still beat MapReduce at most tasks. He hasn't changed his mind.
"Every database vendor wants to claim that they're doing Hadoop because it's the popular thing," he said. "There's too much FUD. SQL databases still work pretty well."
DeWitt leads a database research lab at Madison that is helping Microsoft with R&D for its upcoming Parallel Data Warehousing version of SQL Server 2008 R2 , formerly known as Project Madison.
As such, he said that the new edition of SQL Server will add some analytic functions that roughly mimic some of the features of MapReduce/Hadoop.
The additions are the result of incorporating technology from DATAllegro, which Microsoft acquired , not Hadoop, DeWitt said.
He said does acknowledge, however, that MapReduce/Hadoop is better at keeping long-running queries from crashing than SQL.
Because of that, Microsoft may eventually try to incorporate those capabilities into future data warehousing-oriented versions of SQL Server, he said.
That would likely be a Microsoft-led effort, rather than a licensing of Hadoop's open-source code, which is managed by the Apache Software Foundation.