My background - 4 weeks old in the Hadoop world. Dabbled a bit in Hive, Pig and Hadoop using Cloudera's Hadoop VM. Have read Google's paper on Map-Reduce and GFS (PDF link).
I understand that-
Pig's language Pig Latin is a shift from(suits the way programmers think) SQL like declarative style of programming and Hive's query language closely resembles SQL.
Pig sits on top of Hadoop and in principle can also sit on top of Dryad. I might be wrong but Hive is closely coupled to Hadoop.
Both Pig Latin and Hive commands compiles to Map and Reduce jobs.
My question - What is the goal of having both when one (say Pig) could serve the purpose. Is it just because Pig is evangelized by Yahoo! and Hive by Facebook?
Check out this post from Alan Gates, Pig architect at Yahoo!, that compares when would use a SQL like Hive rather than Pig. He makes a very convincing case as to the usefulness of a procedural language like Pig (vs. declarative SQL) and its utility to dataflow designers.