Difference between pig vs hive vs sql
| Pig | Hive | Sql |
|---|---|---|
| Apache Pig also allows developers to follow multiple query approach, which reduces the data scan iterations. |
Hive statements are similar to Structured Query Language (SQL) and limitations of Hive Query Language(HQL) in terms of the commands that it understands, it is still very useful. |
Structured Query Language has been a programmer’s companion for decades. It was the real solution for extractingdata for further processing. |
| PigLatin is procedural to a large extent. |
Hive is built with an analytical focus. | Structured Query Language is Informative. |
| Pig requires that programmers to learn something on top of structured query language(SQL). |
Hive provides an open source implementation of MapReduce. |
Structured Query Language demand of storing data in a strict relational database schemas and its declarative nature often deflects focus from the ultimate purpose to extract data for analysis. |
| It offers a number of advantages in terms of declaring execution plans Extract, transform, load(ETL) routines and pipeline modification. |
Hive lacks update and delete functions but is superfast in reading and processing huge volumes of data faster than SQL. |
The DBMS systems that SQL operates on, are considered to be faster than MapReduce. |