NoSQL and Big Data Databases: 3 Advantages and Disadvantages to Keep in Mind

NoSQL and Big Data Databases

For years, relational database management systems (RDBMS) like MySQL have been the standard for administrators, developers, and other IT professionals that specialize in database management. Nowadays, organizations are collecting information at such a volume, variance and velocity that these systems just are not equipped too handle it. The data is so large, and coming in from so many places at such a fierce pace that it exceeds their processing capacity. Big data calls for big database requirements, but luckily, solutions like NoSQL have emerged to pick up the slack.

 What is NoSQL?

Sometimes referred to as “Not Only SQL”, NoSQL is a relatively new type of database being increasingly used for big data implementations and real-time web applications. An open-source concept, it thrives at handling large amounts of data, particularly the unstructured information RDBMS programs struggle to support without major formatting tweaks. NoSQL powers a number of big data solutions, including those offered by Amazon, Oracle, and other vendors.

NoSQL Advantages

NoSQL isn’t all hype. There is substantial sizzle behind this trend. Here are three reasons it makes an ideal big data database:

1. Made for big data. By design, NoSQL is capable of storing, processing, and managing huge amounts of data. This not only includes the structured data you collect from your web form or at the point-of-sale, but text messages, word processing documents, videos and other forms of unstructured data as well. While RDBMS applications are growing in terms of what they can handle in capacity, they are largely outclassed and outmatched by NoSQL.

2. Seamless scalability. Traditionally, many organizations addressed the need for scaling up by throwing money at the problem. When you needed to accommodate more data, you simply bought a bigger server with bigger capacity. Big data databases are designed with scalability in mind, offering a convenient way for companies to transition to new nodes both on-premise and in the cloud as well – all while maintaining the high level of performance and availability such mission-critical applications require.

3. Cost effective data processing. Commercial RDBMS solutions like SQL Server tend to perform best when paired up with commercial servers, which means you could up shelling out a lot of cash depending on the number of machines in your cluster. NoSQL, on the other hand, thrives on low-cost commodity hardware. As a result, it offers what is often a significantly more cost effective way to store and process data in comparison to its proprietary competitors.

NoSQL Drawbacks

NoSQL delivers the type of flexibility, scalability, and reliability that affords organizations the opportunity to do big data more efficiently, and at a lower cost. Having said that, there are some potential disadvantages to take into account.

1. Lack of familiarity. Hitched on the shoulders of big data, NoSQL is slowly but surely piggybacking its way to way mainstream viability. However, RDBMS tools have been around forever in IT years and form the only category of databases many businesses know. Like any new technology, NoSQL can be a tough sell for senior-level executives who are coddled in the comfort and familiarity of their existing systems.

2. Management challenges. Big data tools aim to make managing large amounts of information as simple as possible. But ask any administrator who is responsible for interacting with the databases behind these tools and most will tell you that we still have a long way to go in the simplicity department. NoSQL, in particular, has a reputation for being challenging to install, and even more hectic to manage on a day-to-day basis.

3. Limited expertise. Based on maturity alone, there are countless administrators that know the fundamentals of MySQL and RDBMS software in general like the back of their hands. With big data being a relatively new concept, it’s fair to say that even a specialist only has limited knowledge of NoSQL. This is a critical factor that can make assembling a staff of skilled data administrators and engineers quite the daunting task.

NoSQL is one of the most important components in today’s vast and versatile data architectures. How well your team knows this database solution will likely say a lot about the results you get from your big data efforts.

NoSQL and Big Data Databases: 3 Advantages and Disadvantages to Keep in Mind
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