![]() The Spring Data Document (or DATADOC) framework makes it easy to write Spring applications that use a Document store by eliminating the redundant tasks and boiler place code required for interacting with the store through Spring’s excellent infrastructure support. Enterprise class support, training, and consulting available.Store files of any size without complicating your stack.Flexible aggregation and data processing.Atomic modifiers for contention-free performance.Scale horizontally without compromising functionality.MongoDB (from “hu mongous”) is a scalable, high-performance, open source, document-oriented database. if you were storing an essay, all the chapters are intrinsically linked to the essay as a whole document, and a single chapter doesn’t make much sense as an individual object on its own). ![]() For example, if the data you are modelling cannot naturally be stored as “documents”, then a Document-oriented DB probably isn’t the best solution (an easy way to think about whether the model can be stored as a document is to think of it being stored on paper – does it make sense for all the elements to be intrinsically grouped in to a single document? E.g. This article will look at integrating the Document oriented database MongoDB with a Spring MVC Web Application – it is important to note that due to the nature of Document based storage solutions, they are not applicable for all problems. Within the NoSQL space there are several different implementation options (Graph based DBs such as Neo4J, Wide Column DBS such as Cassandra and Haddop, Document based DBs such as MongoDB and CouchDB) and careful consideration is needed before choosing an implementation. This in turn has lead to huge growth in the NoSQL space, with leading web companies such as Facebook, Google, Twitter, Reddit, etc adopting NoSQL solutions. With the explosion in the amounts of data being generated in recent years, more and more organisations are looking at alternative data storage options to the traditional relational model.
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