Preface Large scale and high-concurrency ...

Preface Large scale and high-concurrency applications and search engines have appeared to be facing challenges in using the relational database to store and query dynamic user data known as Big Data. NoSQL has emerged as an advance database technology capable of meeting these requirements. Some experts classify them according to their data model such as Aggregate Oriented and Non-Aggregate Oriented, while others outline them as four major types i.e. Key-value, Document databases, Column-oriented databases and Graph databases. Big Data needs innovative technology to extract the hidden potentials on them which are unlimited. One of such Big Data technologies is Apache Hadoop, an open-source software framework. Apache Hadoop and its modules and components such as HDFS, Storm, Zeppelin, HBase, and Hive are capable to handle large amounts of data. New methodologies like IVIS4BigData or CRISP4BigData to handle the information visualization from raw data into visual views and to deal with analysis processes and projects, beginning with the business process understanding to Archiving and Retention. Another such Big Data crunching application is Next Generation Sequencing (NGS) which is capable of dealing with Terabytes or Petabytes of genome data requiring high computational power. Further success of Cassandra for Facebook, Google BigTable for Google, Dynamo for Amazon, MongoDB for eBay and many other NoSQL tools have shown great performance for practical scenarios where data is continuously growing. Lots of applications are already migrated from relational database systems to NoSQL database, since NoSQL is capable of supporting unstructured text and multiple data structures, rapid change over time, flexible schema pattern. As a semi structured source, NoSQL can represent data as XML data and it can be accessed in Hybrid manner like SQL/XML language. As a result data migration from SQL to NoSQL and vice-versa is a very interesting area of research in Database technology. There are various techniques of migrating data from the traditional relational SQL-based databases to NoSQL databases. There are translators such as Mongify to migrate data from SQL to MongoDB. Similarly, the tools such as Batch Importer, GEOFF, or the REST batch API can be used for migrating (translation) data from MySQL to Neo4j Server is a good example of SQL-NoSQL interoperability. As increasingly sensitive data is being stored in NoSQL databases, security of database intruders become growing concerns. Security problems of NoSQL database environments are categorized into multiple fields including safeguarding Integrity, Shared data, and compromised clients. Maturing technology of NoSQL databases poses a tremendous opportunity for its adoption in the domain of network security. Research effort to address the issues relating to Data protection, User authentication etc. to improve the built in security mechanisms of the NoSQL databases is the need of the hour. This book in Five Sections will deliberate upon all the facet of NoSQL databases starting from the theoretical foundation of NoSQL database to Hands On in 28 Chapters contributed by renowned scholars from various countries. Ganesh Chandra Deka