Transformation of SQL system to NoSQL system and performing data analytics using SVM

Last decade records a huge amount of data transition going on Internet. Today's world is connected by Social Networking sites which have huge size of databases. Currently, there is no utility existing for transforming SQL databases into NoSQL databases. NoSQL is a new trend; there is no software or utilities that are designed for the desired conversion. Most of the utilities developed, were developed for converting one form of SQL database to another SQL database. To promote Hybrid Database architecture including a Relational Database and NoSQL Database, a Data Adapter system is proposed. It can deal with database transformations using a data synchronization mechanism. It focuses on enabling effective Data Analytics on Scaled-out Object Storage Systems. There is implementation of a Data Analytics Layer on an Object-based Storage Cluster to perform in-place Map-Reduce computation on existing data. It keeps the strengths of RDBMS as ACID properties and at the same time by providing the benefits of NoSQL through a middle layer which keeps track of all running transactions and manages with other layers with concurrent transactions. The Data Adapter uses a SQL layer accepting queries from application services, so that original application remains intact. The Data Adapter also controls query flow during database transformations. An approach that performs computation on existing large-scale data in an Object Storage system without moving data anywhere and outcomes of this approach are analyzed. This outline can deliver strict consistency without affecting scalability and availability of NoSQL Databases.