SQL databases v. NoSQL databases

@article{Stonebraker2010SQLDV,
  title={SQL databases v. NoSQL databases},
  author={Michael Stonebraker},
  journal={Commun. ACM},
  year={2010},
  volume={53},
  pages={10-11}
}
The <i>Communications</i> Web site, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of <i>Communications</i>, we'll publish excerpts from selected posts.<br /><br /><b>twitter</b><br />Follow us on Twitter at http://twitter.com/blogCACM<br /><br />Michael Stonebraker considers several performance arguments in favor of NoSQL databases---and finds them insufficient. 

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References

SHOWING 1-2 OF 2 REFERENCES

The End of an Architectural Era (It's Time for a Complete Rewrite)

The current RDBMS code lines, while attempting to be a "one size fits all" solution, in fact, excel at nothing and should be retired in favor of a collection of "from scratch" specialized engines.

OLTP through the looking glass, and what we found there

Overall, overheads and optimizations that explain a total difference of about a factor of 20x in raw performance are identified and it is shown that there is no single "high pole in the tent" in modern (memory resident) database systems, but that substantial time is spent in logging, latching, locking, B-tree, and buffer management operations.