In this era of the ‘Third Platform’, modern applications now operate in myriad IT environments across social media, mobile computing, big data analytics, and cloud, which makes complex demands on your data management. To overcome these demands, NoSQL, which encompasses a wide variety of different database technologies, was developed in response to a rise in the volume of data stored about users, objects, and products; the frequency with which this data is accessed; and the growing performance and processing needs of businesses.
NoSQL uses a different structure to store data including graph stores and document stores with unique identifiers for every discrete piece of data. In contrast, relational databases were neither designed to cope with the scale and agility challenges that face modern or third platform applications, nor were they built to take advantage of the inexpensive storage and processing power available today. NoSQL can also be distributed across nodes in a cluster, whereas relational databases lack the capability.
Using programmatic languages that enable flexibility and speed, a NoSQL database can absorb unstructured data and enable this data to be queried at speed. Prioritising speed and adaptability over consistency, NoSQL is well suited to big data use cases and clustered infrastructures.
Understanding Factors Affecting NoSQL Performance
Since NoSQL comes in different offerings, different factors affect NoSQL performance. The method and approach of different databases certainly has an impact. For example, a document-oriented database will perform differently to a Graph-based database even when the underlying hardware is similar.
When we look at NoSQL performance, we measure its effectiveness using the following metrics:
As the NoSQL database becomes more complex, it becomes harder to write efficiently coded queries, thus affecting performance. However, NoSQL is also resource-hungry and there is no doubt that its underlying processing power has a large impact on performance.
Harnessing the Power of NoSQL
NoSQL distributed databases are designed to leverage the processing power of clustered commodity hardware; however, specialist enterprise-class infrastructure can also assist in generating better NoSQL performance over and above commodity x86 clusters. NetApp, an established player in Enterprise Storage, has a portfolio of products providing the ideal underlying infrastructure to optimise NoSQL performance.
For example, Apache Cassandra is a massively scalable, open-source, NoSQL database that offers continuous availability, linearly scalable performance, operational simplicity, and easy data distribution across multiple data centres and with cloud availability. It is therefore critical for users to maintain the highest levels of scalability, performance, and uptime for Cassandra workloads. An enterprise can easily scale applications while maintaining maximum performance and uptime, by deploying the Apache Cassandra NoSQL database on various NetApp data storage systems:
Today’s NoSQL database storage must keep up with continuous growth and meet the most demanding capacity requirements. Apache Cassandra is just one of the many examples of NoSQL databases currently validated and supported by NetApp. Others include Couchbase, MongoDB, HBase, Redis, and MarkLogic.
Extracting value from NoSQL databases in the data centre is critical to any business mission. It demands an enterprise-class storage platform that's fast, reliable, and flexible. NetApp solutions deliver high performance, resilience, and scale for NoSQL databases—you can query your unstructured big data, or start handling data from sensors and machines (Internet of Things). With shorter time for rebuilds and consistent performance, even during failure, means adherence to tight service level agreement (SLAs) and even tighter customer requirements.
If you are keen to know more in-depth about NoSQL, this page will be helpful for you!