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MapReduce vs. SQL: It’s Not One or the Other

Rafer sez:
Everyone’s stuck in the speeds, feeds, and optimizations, but the point is money. First, money in the sense of building great businesses and self-cannibalizing them to keep them great. Second, professional analysts like Monash always stick up for their clients, in this case the database incumbents. Stonebraker’s motives [update: spellchecking by @joshu] are likely purer. He’s one of the biggest brains the Bay Area has ever produced, but I’m going to speculate he’s emotionally over-invested in structured DBs.

Most of the tasks being benchmarked were optimized for SQL DBs because they were the most cost-effective systems when those business processes were designed. We will be soon assigning them to the long, slow profitable declining category of “legacy systems.” As with any other transition, the change will not be universal. Mainframes are still the best for a number of tasks but no longer for the bulk of them.

Lookery and hundreds of other companies, many cloud-hosted, are building new business processes that are optimized for MapReduce and similar architectures. In many — even most — cases, these business processes will be far more cost-effective than the ones they will replace. New incumbents will arise, new benchmarks written, and new statistics reported by analysts with new biases.

Companies invested in SQL apps that can be replaced, most often indirectly, by MapReduce-esque apps need to start self-cannibalizing.