Big data is in, and consequently, relational databases are out. That’s what everyone’s saying, anyway, and it’s not hard to see why: traditional databases do, after all, have a great deal of difficulty with the massive and unpredictable flows of information that go hand-in-hand with unstructured data. It’s gotten to the point where there are many who believe NoSQL might replace SQL entirely, rather than simply existing as an alternative: this belief is inaccurate for a number of reasons, not the least of which is the fact that the SQL query language (or at the very least an approximation) can be utilized in NoSQL with relative ease.
But that’s neither here nor there.
See, while there’s no denying that NoSQL databases are incredibly disruptive, with some very clear advantages in their implementation; at the same time, the technology also has a number of shortcomings and limitations. Today, I’d like to have a look at some of the chief advantages of a NoSQL implementation in light of the disadvantages.
It’s More Scalable
NoSQL’s Elastic Scaling is precisely what makes it so well-suited for big data. Relational databases tend often to ‘scale up’: they add larger, more powerful servers as the database load begins to increase. In the case of big data – which is likely to grow at a breakneck pace- this simply isn’t a viable choice. It’s thus far better to ‘scale out’ instead; distributing the database across multiple hosts in order to efficiently manage server load.
A NoSQL database is considerably less restricted than an SQL database, mainly because it’s not locked into any one specific data model (this also forms the crux of one of its chief disadvantages, but more on that in a moment). Applications can store data in virtually any structure or format necessary, making change management a breeze. Ultimately, this means more up-time and better reliability. Contrast this against relational databases, which must be strictly and attentively managed; where even a minor change may result in downtime or a reduction of service.
NoSQL databases tend more often than not to be considerably less complex and considerably simpler to deploy than their relational cousins. This is because, as noted by Tech Nirvana, they’re “designed from the ground up to require less management, with automatic repair, data distribution, and simple data models.” All these factors together ultimately lead to a database which requires considerably less overhead management.
It’s Cost-Effective and Open-Source
The servers utilized in a NoSQL implementation are typically cheap, low-grade commodity devices, as opposed to the oft-expensive servers and storage systems required in relational databases. That’s not the only thing that drives down the cost, either. NoSQL is entirely open-source, meaning generally higher reliability security, and speed of deployment.
The Cloud’s the Limit
NoSQL meshes naturally with cloud computing. This is due to a couple of factors. Foremost among these is that NoSQL’s horizontal scaling meshes extremely well with the cloud, allowing them to take full advantage of cloud computing’s elastic scaling. In addition, the ease of deployment and management within a NoSQL database (and its focus on big data) make it a prime partner for cloud computing, allowing administrators to focus more on the software side of things rather than having to worry about what hardware they’re using.
It Has a Very Narrow Focus
One of the primary reasons that NoSQL will never wholly replace SQL is that it was never meant to do so. NoSQL databases have a very narrow focus: they are designed primarily for storage, and offer very little functionality beyond. When transactions enter the equation, relational databases are still the better choice. Further, NoSQL doesn’t really do so well with data backup on its own.
Standardization and Open Source
That NoSQL is open-source could at once be considered its greatest strength and its greatest weakness. The truth is, there really aren’t many reliable standards for NoSQL databases quite yet, meaning that no two databases are likely to be created equal. Getting a particular implementation to play nice with existing infrastructure can thus be something of a crap-shoot, while support could end up being spotty when compared against a more traditional database implementation.
Performance and Scaling > Consistency
Because of the way data is stored and managed in a NoSQL database, data consistency might well end up being a concern. NoSQL puts performance and scalability first; consistency isn’t really a consideration. Depending on what you’re using it for, this could actually be either a crippling weakness or a powerful strength. In certain situations – such as when you’re dealing with a massive onslaught of unstructured data – this is completely acceptable. In other situations, such as management of financial records, it most certainly is not.
A General Lack of Maturity
While it’s certainly true that NoSQL isn’t exactly the new kid on the block (the underlying technology has existed for at least ten years now), widespread acceptance of NoSQL still lags; compared to traditional relational databases the technology is still relatively immature. This is reflected also in a lack of developers and administrators with the right knowledge and skills: NoSQL may be administrator and developer-friendly, true, but that means nothing if neither administrator nor developer have the tools or understanding to address it.
Relational databases are much better established in the enterprise world, and thus enjoy more functionality, greater acceptance, and a wealth of professionals who actually understand how to manage them.
It Doesn’t Play Nice with Analytics
Admittedly, this is a weakness which has been addressed in recent years, with the emergence of startups like Precog. Even so, NoSQL doesn’t necessarily mesh well with traditional BI applications and platforms. It might well be less complex than SQL in many areas, but where analytics is concerned, it has the very real potential to become a complicated, difficult-to-decipher behemoth.
NoSQL databases have gained a great deal of popularity over the past several years, with the emergence of big data and the ever-increasing prevalence of the cloud. While the technology is great for dealing with many difficulties surrounding unstructured data, it’s nevertheless limited in a number of other key areas. An administrator must thus consider carefully which type of database best suits their needs before committing to one implementation or the other – the wrong choice could have disastrous consequences.