While there have been some truly misguided mapreduce implementations, mapreduce is just a computation model that isn't inherently slower than others: A relational aggregation of the type you get with SQL like:
select foo, count(*) from bar group by foo
...is essentially a mapreduce, although most databases probably don't use a reduce buffer larger than 2. (But they would benefit from it if they could use hardware vectorization, I believe.)
Mapreduce works great if you are already sequentially churning through a large subset of a table, which is typically the case with aggregations such as "count" and "sum". Where mapreduce is foolish is when you try using mapreduce for real-time queries that only seek to extract a tiny subset of the dataset.
Mapreduce works great if you are already sequentially churning through a large subset of a table, which is typically the case with aggregations such as "count" and "sum". Where mapreduce is foolish is when you try using mapreduce for real-time queries that only seek to extract a tiny subset of the dataset.