- March 21 2016
NoSQL Live Training
Note :- We are recording the NoSQL videos, All the videos will be available for purchase on the website max by April 1st week for $75
Off late the concept of Big Data is a buzz word in the Industry.Of all the modules in BigData,as always Databases are important, too supports a host of latest Databases like Document Databases,Graph Databases,Key databases.Normal SQL queries doesn’t support fetching data from these databases.Next-gen SQL called as NoSQL serves the purpose. NoSQL encompasses a wide variety of different database technologies that were developed in response to the demands presented in building modern applications.
THE MANY FACES OF NOSQL:
Having heard the term “NoSQL”, you could be forgiven for thinking all technologies under this umbrella have the same data model. In fact, NoSQL refers to a whole host of technologies, which store and process data in different ways. Some of the main ways include:
Document Databases :This image from Document Database solution CouchDB sums up the distinction between RDBMS and Document Databases pretty well:
Instead of storing data in rows and columns in a table, data is stored in documents, and these documents are grouped together in collections. Each document can have a completely different structure. Document databases include the aforementioned CouchDB and MongoDB.
Key-Value Stores:Data is stored in an associative array of key-value pairs. The key is an attribute name, which is linked to a value. Well-known key value stores include Redis, Voldemort (developed by LinkedIn) and Dynamo (developed by Amazon).
Graph Databases:Used for data whose relations are represented well in a graph. Data is stored in graph structures with nodes (entities), properties (information about the entities) and lines (connections between the entities). Examples of this type of database include Neo4J and InfiniteGraph.
Columnar (or Wide-Column) Databases:Instead of ‘tables’, in columnar databases you have column families, which are containers for rows. Unlike RDBMS, you don’t need to know all of the columns up front, each row doesn’t have to have the same number of columns. Columnar databases are best suited to analysing huge datasets- big names include Cassandra and HBase.
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