Big companies, including Amazon, Google, Facebook and Yahoo, first adopted NoSQL for in-house solutions due to the lack of RDBMS feature support for their ever-changing needs. By providing weak consistency and optimizing for certain use cases, they’re able to utilize large distributed systems to handle their required workloads. There are five ways that NoSQL handles large workloads differently than do traditional RDBMSs, and in which NoSQL outperforms RDBMSs.
1: Data Volume
NoSQL systems, such as Cassandra, allow scaling out on commodity hardware. This enables them to handle large data volumes. A comparable RDBMS solution from Oracle or Teradata is orders of magnitude more expensive than a NoSQL solution because RDBMSs don’t provide the same guarantees.
NoSQL databases handle the variable demand of Cloud and Big Data effectively. As databases move into virtualized environments, the economic advantages of scaling out on commodity hardware become irresistible. Elastic Scaling refers to the scaling of resources up or down on a need or demand basis. NoSQL databases are designed to expand transparently in order to take advantage of new nodes.
NoSQL databases are generally designed from the ground up and require less management than RDBMSs. Features like automatic repair, data distribution and use of simpler data models lead to lower administrative and tuning requirements. In addition, many programmers are not trained in declarative languages like SQL, but are well versed in procedural languages and in many of the data constructs used in NoSQL databases.
4: Flexible Data Models
NoSQL databases have far more relaxed, or even non-existent, data model restrictions. The rigidity of schema in SQL comes with huge operational overhead and discourages rapid innovation. NoSQL, by relaxing the schema, allows a database system to pivot more rapidly, which allows the system to keep pace with ever-changing demands. For example, the same change that may have taken months of planning for an SQL can now be completed in mere minutes for a NoSQL
Various NoSQL applications have their own strengths and weaknesses that allow you to choose the system most appropriate for your needs, whether it’s a simple key-value store or a graph database model.
More on NoSQL database solutions in the next post.
The goal of a business, of course, is to make money, and that’s accomplished by providing more for less. NoSQL databases drastically reduce the need for insanely big machines. Typically, they use clusters of cheap commodity servers to manage exploding data and transaction volumes. The cost-per-gigabyte or transaction/second for NoSQL can be considerably lower than the cost for RDBMSs, thereby dramatically reducing the cost of data processing and storage. Another area of key savings is in manpower. By lowering administrative costs one can free up developers to code new features that will generate more revenue.