Welcome to Day 4 (Believe me it will take more than one day) of MongoDB Tutorial

SQL is back. Not just because writing glue code to kludge together NoSQL tools is annoying. Not just because retraining workforces to learn a myriad of new languages is hard. Not just because standards can be a good thing.

But also because the world is filled with data. It surrounds us, binds us. At first, we relied on our human senses and sensory nervous systems to process it. Now our software and hardware systems are also getting smart enough to help us. And as we collect more and more data to make better sense of our world, the complexity of our systems to store, process, analyze, and visualize that data will only continue to grow as well. 

KeyValue Databases e.g Riak, Redis, Berkeley DB, CouchBase etc.

Document Databases e.g MongoDB, CounchDB, OrientDB etc.

Column Family Databases e.g Cassandra, HBase, Amazon DynamoDB etc.

Graph Databases e.g Neo4J, OrientDB etc. 

Stairway to XML

XML has been part of the SQL Standard since 2003, and is essential for any DBA because so many of the dynamic management views return XML data. Now that the industry is more used to data defined by document markup, it is becoming more important than ever for Database Developers and DBAs to understand the technology and to know where it makes sense to use XML. In this book, originally a series of articles on SQLServerCentral.com, Robert Sheldon flexes his talent to make the complicated seem simple. 

How we reindexed 36 billion documents in 5 days within the same Elasticsearch cluster 

This article aim to make an objective comparison from SQL and NO-SQL technology and try to clarify some unclear aspect to help people to choose it’s backend knowledgeably. 

NOSQL for Dummies