Community Platform
PRO PROGRAM

Victor Badoo

Interests
  • Cyber-security
  • Data analytics
  • Data warehousing
  • Database management systems
    • more...
This Year
No Points
Total
825 Points
MIS Badge

Click here
to validate the recipient

NOSQL

nosql-databases

NOSQL or Not Only SQL is an upcoming category of highly scalable database management systems.  Its main feature is its non-adherence to relational database concepts. NOSQL does not use SQL to query data nor does it follow strict schemas such as relational models.

There are four main emerging SQL categories:

  • Key-Value Stores are the simplest among NoSQL databases. Single items in the data base is stored as an attribute name (or “key”) combined with its value. Examples include Dynamo, Riak, Voldemort,
  • Wide Column / Column Familes (Big Table) is based on Google’s BigTable paper  that stores data tables as sections of columns instead of rows of data seen in relational DBMS. Examples includes HBase, Hyperable, and Cassandra.
  • Document Database pair each key with a complex data structure known as a document. Examples include MongoDB and CouchDB.
  • Graph Databases are the most complex among NoSQL databases. Graph databases utilizes graph theory to represent and store data.  Graph databases are very useful in storing information about social connections, road maps, network topologies, for instance.  Examples include Neo4j, AllegroGraph

NOSQL in the Classroom:

While there many benefits of using Relational databases, one of the issues we touch on in my MIS*2502 Data Analytics course is the scalability of relational databases. As data gets bigger, the speed to retrieve it gets increasingly slower due to the large amount of joins that are required. NoSQL addresses this issue by having superior performance over SQL in the ability to handle large volumes of structured, semi-structured, and unstructured data.  Due to the nature of NoSQL, big data industry is shifting their focus from handling large amounts of data to real-time analytics.

NOSQL in Practice:

Amazon, for example, introduced its DynamoDB as part of the Amazon Web Services portfolio. Amazon uses DynamoDB to sell NoSQL cloud database services. This enables Amazon to offer fast, predictable performance with seamless scalability. This allows developers who start small to scale-out with ease as the amount of data increases. What makes DynamoDB unique among Amazon’s other web services is that developers can purchase a service based on throughput instead of storage.

References

Gartner. (2014, Feburary 28). A Tour of NoSQL in Eight Use Cases. Retrieved from Gartner: http://my.gartner.com/portal/server.pt?open=512&objID=260&mode=2&PageID=3460702&resId=2673515&ref=QuickSearch&sthkw=nosql

ITBusinessEdge. (2014). Five Reasons Scale-Out SQL Will Make Waves in the Enterprise. Retrieved from ITBusinessEdge: http://www.itbusinessedge.com/slideshows/five-reasons-scale-out-sql-will-make-waves-in-the-enterprise.html

MongoDB. (2014). NoSQL Databases Explained. Retrieved from MongoDB: http://www.mongodb.com/nosql-explained

Amazon. (2014). AWS Amazon DynamoDB – NOSQL Cloud Database Service. Retrieved from Amazon DynamoDB : https://aws.amazon.com/dynamodb/

 

 

 

Skip to toolbar