By Wally McDermid
Data lakes offer an appealing and practical option for organizations dealing with enormous (and exponentially growing) volumes of unstructured data. But if you’re not vigilant, those lakes can quickly turn into swamps, leaving you to wade through the muck to find the data you need. That’s time-consuming and costly, and it also can leave your organization vulnerable to new security concerns.
How can you keep your data lake from becoming a swamp? Object storage ensures your data stays easy to find and use — while keeping it safe from threats.
What is a data lake vs. a data swamp?
At its most basic level, a data lake is a system or repository of data stored in multiple formats and coming from many sources. Gartner’s definition goes further to describe a data lake as “a concept consisting of a collection of storage instances of various data assets. These assets are stored in a near-exact — or even exact — copy of the source format and are in addition to the originating data sources.”
A data swamp, by contrast, is a pile of muck. It’s an assembly of data plopped in one place with no categorization or taxonomy. If you need something from it, you’re just going to have to wallow through the sludge with your fingers crossed.
This approach is obviously not efficient, nor is it safe. When you don’t know what data you have or where you have it, keeping it secure is next to impossible. Clearly, no one wants a data swamp, but the unfortunate reality is that it’s all too easy for a data lake to turn into something rivaling Okefenokee.
The key to keep this from happening is to maintain cleanliness and organization in your data lake — and that’s where object storage can play an important role.
How object storage helps you avoid a data swamp
Without structure (without metadata), your massive “body” of data isn’t a lake. It’s a swamp. Not only can you not find what you need, but you might not even know where to look in the first place. Imagine you’re wading through a literal swamp trying to find something you dropped, and you get a pretty good idea of the scenario.
Object storage excels here in that it organizes information into containers of flexible sizes — aka objects. Each object includes the data itself as well as associated metadata, and it has a globally unique identifier rather than a file name and path (which is the way file storage works).
These systems can be augmented with custom attributes to handle additional file-related information, which makes finding the information you need that much easier. You’re no longer trying to wade through a thick soup of mud and gunk, metaphorically speaking.
With object storage, there’s no limit on data volume, which is important considering data lakes can quickly reach petabyte-scale and beyond. You need a solution that can handle immense capacity, scaling seamlessly and horizontally as data continues to proliferate and be pulled in from various sources.
The competitive advantage of using object storage for data lakes
It’s not just that data becomes harder to find and identify when you veer toward data swamp status. It’s also that you’re leaving valuable insights on the table. Being able to fully reap the business insights within data lakes depends on both analytics tools and the storage repository where you’re housing the data.
The repository must be able to process data from various sources — with just the right performance— and it must also be able to scale in terms of performance and capacity to ensure that data is accessible to applications, tools and users.
Object storage meets this need. The right solution can provide the scalability, flexibility and lower cost that organizations require to keep their data lake clean and gain a wealth of other benefits from it.
For a look at real-world applications of object storage, read about how we helped HPE power an intelligent data lake and how Scality RING achieved a milestone in continuous operations and recovery point objective (RPO) for a major U.S. bank.
Storage that doesn’t require a pair of gaiters (and is free of gators!)
While a little silly, the swamp metaphor is a great one for understanding just how difficult it can be to find, use, and protect your data from lurking threats if you don’t have a strategic approach in place. It’s difficult to plan ahead and stay on top of things when the amount of data coming into your organization is continually increasing, and it’s not all one uniform shape, size and format.
That’s what makes object storage so ideal for use in data lakes. It stores both unstructured and structured data in a way that’s accessible and organized, so you you don’t have to spend valuable resources searching. Plus, when you know exactly what data you have and where it is, properly securing and gleaning useful insights from it becomes possible. When it comes to something as valuable as data, I’d take crystal clear over murky any day — how about you?
Scality helps organizations solve the challenges of large-scale data, once and for all. RING offers unlimited, independent scale-out of capacity and throughput performance. Learn more about how Scality RING can help you bypass the swamp and create a pleasant data lake you’ll be happy to visit.