Most traditional databases use Relational Database Management Systems (RDBMS) to handle relational data. RDBMS generally work well and it is a mature technology that keeps developing. Using this approach for data management is a good choice, if the data size permits it and the data type is relational.
But what if your data are not relational or you are dealing with a huge amount of data, so called Big Data? What if you are unable to save it in an RDBMS?
Than the solution is NoSQL databases.
Main players in the field of NoSQL, ‘not only SQL’, systems include Apache’s Cassandra , MongoDB or Hadoop. But, there are multiple other providers that offer quality products and the number of applications is continuously growing.
NoSQL database management systems don’t use relational data models and, consequently, don’t use SQL as the query language. They are an excellent choice for managing large data volumes that don’t require structure. For example, working with Big Data often requires to store or record data objects. Most of the time, the users are less concerned with storing the information in ordered tables rather than having them merely available for fast access and usage.
One of the outstanding NoSQL database is Hadoop. This system is distributed from the ground up. Adding additional nodes increases the capacity of data management. It works well with structured and unstructured data.
In addition, Hadoop supports numerous serialization and data formats, which include for example Text, Xml, Json, Avro and others.
Tasks that may require NoSQL solutions like Hadoop include, for example, product catalogs with multiple non-relational tables per product type, data that were generated through machines or document indexing data.
Document databases which include MongoDB or CouchDB are collections of documents with key-value collections. Document databases are very useful for natural data modeling and predications. These applications are known to be programmer and web friendly, highly capable for rapid development and provide good ‘create, read, update and delete’ (CRUD) functionality.
Graph Databases such as Neo4j or InfoGrid use nodes and relationships as data and represent great solutions for complex graph problems. They allow rapid data processing of bigger size data.
NoSQL databases are becoming increasingly important, and when used properly, can provide significant benefits.
However, organizations ought to be aware of that most NoSQL alternatives are in pre-production versions with many key features yet to be implemented.