Remove 2016 Remove Java Remove Relational Database Remove Unstructured Data
article thumbnail

Dynamic Typing in SQL

Rockset

As Peter Bailis put it in his post , querying unstructured data using SQL is a painful process. We at Rockset have built the first schemaless SQL data platform. Contrast with Java and C, which are statically typed. In this post and a few others that follow, we'd like to introduce you to our approach.

SQL 40
article thumbnail

Difference between Pig and Hive-The Two Key Components of Hadoop Ecosystem

ProjectPro

Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. What is Big Data and Hadoop? Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data.

Hadoop 52
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What are the Pre-requisites to learn Hadoop?

ProjectPro

There have been several headlines about various big data jobs recently- Best Salary Boost in 8 years awaits US professionals in 2016, STLToday Geeks Wanted! Apart from this, Hadoop has high level abstractions tools like Pig and Hive which do not require familiarity with Java. The US will soon be flooded with 1.9

Hadoop 52
article thumbnail

5 reasons why Business Intelligence Professionals Should Learn Hadoop

ProjectPro

Professionals who have learnt Hadoop have now started integrating Hadoop with DW's, analytic tools, web servers, data visualization tools, reporting tools and analytic databases. The present day RDBMS are perfect for querying structured data and people are well acquainted with their technicalities. PREVIOUS NEXT <

article thumbnail

Healthcare Big Data Projects, Applications and Examples

ProjectPro

.” By the end of 2016, the number of health records of millions of people is likely to increase into tens of billions. Thus, the computing technology and infrastructure must be able to render a cost efficient implementation of: Parallel Data Processing that is unconstrained.