Data Modeling ,moving from SQL to NoSQL in the enterprise lecture

Very interesting lecture about data modeling and moving MySQL to NoSQL

Summary
Kenneth M. Anderson shares some of the data modeling issues encountered while transitioning from a relational database to NoSQL.
http://www.infoq.com/presentations/MySQL-NoSQL-Data-Modeling

Projections in Vertica

Projections... You probably have a good idea of what that means already. Who remembers Plato's cave from high school? It's basically a group of people locked in a cave, staring at a blank wall all the time. All they see on that wall, are shadows of objects in the real world, projections if you will. Plato argued that, for these prisoners, these projections are as close as it gets to reality. However, people who reason about reality, and not just absorb it, free themselves from the cave. And can perceive reality as it really is. Not just its projections. 

In a relational database, you typically have tables, containing your data and its relations. This is reality. If you want to see it from a particular angle, you can project your data into a view. A view might be a subset of columns of a table or a combination of some columns of one table, with some other columns of another table. These things exist in Vertica as well, and they are called projections. But it pushes this notion one step further. In Vertica, there are no tables, only projections. And a collection of projections can represent a table, or multiple tables.  

So Vertica's idea of a projection is really Plato's cave turned inside-out. There is no reality. Only a collection of projections from which we can create that reality if we need to. Sounds familiar? 

SQL is what’s next for Hadoop: Here’s who’s doing it.

SUMMARY:

More and more companies and open source projects are trying to let users run SQL queries from inside Hadoop itself. Here’s a list of what’s available and, on a high level, how they work.

Vertica loading best practices

Vertica loading best practices from Zvika Gutkin

Vertica mpp columnar dbms

Vertica mpp columnar dbms from Zvika Gutkin

Installing and comparing MySQL/MariaDB, MongoDB, Vertica, Hive and Impala (Part 1)

A common thing a data analyst does in his day to day job is to run aggregations of data by generally summing and

averaging columns using different filters. When tables start to grow to hundreds of millions or billions of rows, these operations become extremely expensive and the choice of a database engine is crucial. Indeed, the more queries an analyst can run during the day, the better he can be at understanding the data.

SQL, NoSQL, BigData in Data Architecture

All about how to build "Data Architecture" using SQL, NoSQL and BigData technologies and how to evaluate them.

SQL, NoSQL, BigData in Data Architecture from Venu Anuganti