Serverless Data Architecture: The Modern Path to Digital Transformation

When it comes to digital transformation, data architectures have gotten short shrift.

Many enterprises have focused on modernizing by moving applications to the cloud, or building ecommerce offerings (if they are retailers). But in many cases, data has been left out of the digital transformation story because data systems tend to be large, monolithic, fragile, and difficult to deal with—in other words, there are significant risks to the business if the modernization process doesn’t go as planned. Many companies have turned their attention to easier-to-manage projects, leaving data platform modernization as a challenge for a later time.

I’d like to discuss a couple of misconceptions that can hinder data architecture modernization efforts, and a key approach to enable this kind of transformation.

There is a misunderstanding that often crops up when enterprises are considering digital transformation: it is a monumental, all-or-nothing task that suddenly morphs a traditional company into a modern, digital enterprise.

But think about how, from a high-level viewpoint, retailers transformed themselves. A traditional brick-and-mortar retailer didn’t just reboot itself and, voila, it’s an ecommerce company. Rather, ecommerce started out accounting for, say, 2% of sales, then 10%, then 20%, and so on.

It’s the same for most enterprises across verticals. Transformation is a step-by-step process that usually starts small—one initiative at a time (from a project to a program, to, eventually, a platform).

There is another misconception that still exists: innovation is driven from the top down. Generally, however, technology leaders optimize and scale successful processes that have started within their organization, and create the platforms for innovation that arise from projects. But those projects are usually built by developers. Digital transformation bubbles up from experiments that start small and, if they’re successful, often need to scale fast. This presents a challenge, particularly when you think about modernizing an organization’s data estate.

For digital transformation to succeed, developers require the ability to quickly start a modest project and be prepared for it to grow explosively when needed—without having to pause and perform scalability testing, or worry about how much funding the project will take, or how much latency it might introduce into a system. Spread these requirements over multiple new projects, and the demands for powerful, scalable, and easy-to-use data platforms become critical to success.

However, databases for a long period of time made this kind of work challenging. Scaling up and down took time and effort, which often led to costly overprovisioning.

A select group of cloud databases, including services provided by DataStax and MongoDB, is making it easier for developers to focus on their modernization projects–without the distractions of provisioning, scaling, and other aspects of data management–by offering “serverless,” or “pay-as-you-go,” data.