The Big Data explosion in recent years has spawned a number of new platforms, tools, and technologies for dealing with the volume, variety, and veracity of unstructured data. One of the most popular technologies to hit the stage has been NoSQL. This is a technical term that means either “No SQL” or “Not only SQL.” As the name itself implies, NoSQL suggests a certain pre-conception against the long dominant SQL paradigm.
SQL stands for Structured Query Language, dates back to the 1970s, and is associated with the relational database model (RDMS). To its credit, SQL has been a long-established workhorse within the data management industry, based on a model of data tables set up on rows and columns that could be queried and matched. SQL was the mainstay of database technology for decades. These database architectures were ‘structured’ which meant the data was organized in a uniform format and varied little over time.
On the other hand, NoSQL operates on the premise of the Key-Value Pair (KVP) – a framework where each record has a primary key and a collection of values (bins) associated with that record. NoSQL databases have grown rapidly in popularity over the last several years and the market outlook is great. NoSQL has emerged, in fact, as the preferred choice for mobile and web development.
New technologies often create splits between two opposing camps – between the guardians of the “tried and true” methods, on one hand, and the new trailblazers who embrace the latest and greatest, on the other. But NoSQL vs. SQL shouldn’t morph into a debate; both technologies have their strengths and weaknesses relative to the needs of each business. What we aim to do in the following is to show that NoSQL and SQL (aligned closely below with relational DBs) really represent two entirely different approaches to data management, and that the choice ultimately depends on what your business is trying to accomplish – especially relative to Big Data.
Here’s what you need to know!
NoSQL scales easily across servers, cloud instances, and virtual machines
The humongous volumes of data today, along with the growing complexity of physical, virtual, and cloud environments, require a new approaches to managing and wrangling this data and making it available in real-time to high-expectant customers. NoSQL databases are by design built to scale horizontally, which means that they can easily distribute data across a cluster of server instances. This scalability also makes NoSQL easily integrated into the elastic scaling of the cloud. Ease of deployment and management make NoSQL a good match for today’s virtualized environments; this means less need to worry about hardware and more time to focus on software, strategy, and performance.
NoSQL increases competitive advantage & ROI
There are any number of applications for NoSQL data storage and processing solutions today, ranging from user profile stores, to ecommerce sites, to mobile applications. Netflix is one high profile example of a major organization that migrated from Oracle to the NoSQL database Cassandra to help it better stream huge amounts of content to millions of customers worldwide each day. Given the exploding volume and types of data, more and more organizations are finding that NoSQL offers new approaches to data performance as well as IT management. These new paradigms are translating into numerous improved efficiencies, optimizations, and cost savings. In fact, a growing number of market examples show organizations using NoSQL technology to increase their competitive advantage and overall ROI.
NoSQL is riding a strong market wave
The NoSQL market is a formidable one with projected growth forecast to reach $3.4 Billion in 2020, representing a compound annual growth rate (CAGR) of 21% for the period 2015 – 2020. And a number of leading NoSQL, such as Couchbase, MongoDB, Amazon, MarkLogic, etc. are leveraging agreements with leading application industry players like Facebook, Google, Twitter, and Flipkart to keep growing the market. These trends along with the massive data expected from Internet of Things, means that business leaders would be well advised to look seriously at NoSQL and start taking measures to adopt the latest benefits of this technology.
SQL is ubiquitous and fairly straightforward to learn
SQL is run in programs that reside within mainframes, PCs, laptops, servers, and even mobile phones. It also runs in local systems, intranets, and on the internet. Databases using SQL can be moved from one device to another without any problems. SQL is also not object-oriented, but consists of English statements, making it fairly easy to learn and understand a SQL query.
Relational DBs are good at what they do
Relational DBs are good at performing structured data and transactional, high performance workloads. The offerings are proven and mature and there are a wide variety of tools and resources available to support this model.
SQL & Relational DB knowledge exists throughout most organizations
The relative ease of use of accessing and managing data in rows and columns is a plus. Data security is also more easily maintained in a relational environment where certain sensitive tables can be “hidden” with their own authorization controls. Relational DBs are ubiquitous in organizations today and the skill sets are specialized but still readily available. Many folks in business operations have at least some familiarity with SQL and likely have worked in the table environment of a relational DB.
SQL & Relational DB add-ons are available
More and more alternative DBs are finding value in providing SQL interfaces to meet the needs of this tried and true technology. Hadoop is a case in point. Though it represents a new paradigm in data management, more and more tools have emerged to make Hadoop data accessible through the ever familiar SQL language. In fact, SQL-on-Hadoop is now becoming a standard protocol for many platforms and is expected to continue experiencing strong growth in the Big Data market.