NoSQL (Not Only SQL)

NoSQL database, also called Not Only SQL, is an approach to data management and database design that's useful for very large sets of distributed data.  

NoSQL, which encompasses a wide range of technologies and architectures, seeks to solve the scalability and big data performance issues that relational databases weren’t designed to address. NoSQL is especially useful when an enterprise needs to access and analyze massive amounts of unstructured data or data that's stored remotely on multiple virtual servers in the cloud. .  

Contrary to misconceptions caused by its name, NoSQL does not prohibit structured query language (SQL). While it's true that some NoSQL systems are entirely non-relational, others simply avoid selected relational functionality such as fixed table schemas and join operations. For example, instead of using tables, a NoSQL database might organize data into objects,key or tuples.

Arguably, the most popular NoSQL database is Apache Cassandra. Cassandra, which was once Facebook’s proprietary database, was released as open source in 2008. Other NoSQL implementations include SimpleDB, Google BigTable, Apache Hadoop, MapReduce, MemcacheDB, and Voldemort. Companies that use NoSQL include NetFlix, LinkedIn and Twitter.

NoSQL is often mentioned in conjunction with other big data tools such as massive parallel processing, columnar-based databases and Database-as-a-Service (DaaS).

Relational databases built around the SQL programming language have long been the top -- and, in many cases, only -- choice of database technologies for organizations. Now, with the emergence of various NoSQL software platforms, IT managers and business executives involved in technology decisions have more options on database deployments. NoSQL databases support dynamic schema design, offering the potential for increased flexibility, scalability and customization compared to relational software. That makes them a good fit for Web applications, content management systems and other uses involving large amounts of non-uniform data requiring frequent updates and varying field formats. In particular, NoSQL technologies are designed with "big data" needs in mind.

But for prospective users, the array of NoSQL database choices may seem confusing or even overwhelming. NoSQL databases are grouped into four primary product categories with different architectural characteristics: document databases, graph databases, key-value databases and wide column stores. Many NoSQL platforms are also tailored for specific purposes, and they may or may not work well with SQL technologies, which could be a necessity in some organizations. In addition, most NoSQL systems aren't suitable replacements for relational databases in transaction processing applications,because they lack full ACID compliance for guaranteeing transnational integrity and data consistency.

As a result, IT and business professionals making database buying decisions must carefully evaluate whether the available NoSQL options fit their business needs. In this guide, you can learn more about what NoSQL software can do and how it differs from relational databases. Trend stories and user case studies document how NoSQL databases can be used to support big data, cloud computing and business analytics applications. And experienced users from companies that have already deployed NoSQL tools offer advice on how to make the technology selection and implementation process smoother.