I think your question can be answered in two ways,
The shorter explanation:
I believe that they are/were independent projects and there was no centrally coordinated goal.They were separated in their own sense when they were first introduced but as they evolved comparison and overlap seems to have been a case.
The detailed explanation:
Pig’s programming language aka Pig Latin is a coding approach that provides high degree of abstraction for MapReduce programming but is a procedural in nature not declarative. Pig Latin code is extended through varied user outlined functions that are written in Python, Java, Groovy, JavaScript, and Ruby. Pig has tools for information storage, information execution and information manipulation.In Hive on the other hand, tables and databases are created first and then data is loaded into these tables. It is more structured, resembles SQL.
Some of the comparison points are given below:
Apache Pig may be a scripting language and Hive may be a SQL like search language.
Hive requires very few lines of code when compared to Pig because of its SQL like resemblance.
Pig has issues in handling unstructured information like pictures, videos, audio, text that's unequivocally delimited, log data, etc.
Pig is faster in the data import but slower in actual execution to a language like Hive.
Pig has no metadata support, (or it is optional, in future it may integrate hcatalog). Hive has tables' metadata stored in database.
So to conclude, the purpose of both are different but under the hood, both do the same, convert to map reduce programs.
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