NoSQL versus SQL Server. Instead of storing data in rows and columns like a traditional database, a NoSQL database management system stores each item individually with a unique key. Because of NoSQL's flexibility and scalability, large organizations have begun using NoSQL databases to store user data. NoSQL databases are frequently being used in cloud computing applications and have become a storage solution for big data.
If you’ve built an application that stores its data in a relational database like MySQL or PostgreSQL, then you’ve likely run into situations where joining two or more large tables becomes very slow and painful. Because our SQL Layer stores its underlying data in our Key-Value Store, it has a unique feature called “Table Groups” that alleviates painful joins and allows your application to stay speedy.
NoSQL. Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontally scalable. Wide Column Store: Hadoop / HBase, Cassandra, Hypertable, Document Store: MongoDB, Elasticsearch
Phoenix: How (and Why) we put the SQL back into the NoSQL. Phoenix is an open source project from Salesforce.com that puts a SQL layer on top of HBase, a NoSQL store. This talk will focus on answering two questions: 1) why put a SQL layer on top of a NoSQL store? and 2) how does Phoenix marry the SQL paradigm back together with the NoSQL world? Salesforce.com uses relational database technology extensively, so a big part of the ?why? for us is to provide developers with a familiar API
What is Hadoop: SQL Comparison - This video points out three things that make Hadoop different from SQL. While a great many differences exist, this hopefully provides a little more context to bring mere mortals up to speed. There are some details about Hadoop that I purposely left out to simplify this video.