An exabyte (EB) is an enormous unit of digital data storage, equal to a massive 1 billion gigabytes (GB) or 1 quintillion bytes. With today‘s relentless explosion of data from all corners of technology and society, the need to measure and grasp storage volumes on the exabyte scale has become increasingly vital. Consumer-level hard drives may only be sized in gigabytes or terabytes, but when it comes to giant cloud data centers, hypersonic networks and bleeding-edge supercomputers, exabyte-class capacities are the new normal.
To comprehend the sheer size of an exabyte, some perspective is helpful. A single gigabyte can hold a few hours of HD video or around 300,000 pages of plaintext documents. Now scale that up a thousand times to a terabyte, which can store up to 6 million document pages. Scale up another 1000 times to a petabyte, and now we‘re talking 6 billion pages filling thousands of whole libraries. Keep scaling, and at an exabyte we reach 6 trillion pages of data – that‘s over 50 million Libraries of Congress!
This aptly demonstrates why traditional digital storage measurements like megabytes (MB), gigabytes, and even terabytes are no longer adequate yardsticks for the world‘s exponentially ballooning data volumes. While megabytes and gigabytes still dominate most consumer applications like PC hard drives, music files and smartphone photos, once we enter the realm of massive cloud server farms, research supercomputers and sprawling metropolitan surveillance systems, the game changes. Global datasphere projections show worldwide data storage demand reaching 175 zettabytes (ZB) by 2025 – that‘s 175 trillion gigabytes, or 175,000 exabytes in a mere 3 years!
The Exabyte Era is Already Here
To put things in perspective, experts estimate the total written works of humankind from ancient times until modernity would comprise just 50 petabytes of data – a tiny fraction of a single exabyte. Yet today, millions of times more data than that is processed every single day by the likes of Google, NSA, and CERN.
The seed that blossomed into the era of big data analytics and machine learning was planted back in the early 2000s when pioneers like Google began assembling what were then considered gigantic data centers to crawl and index the fledgling web. As digital disruption spread across industries, scientific instruments became exponentially more sensor-laden and sophisticated, social media colonized human communication patterns, and smartphones equipped with cameras put video recording devices in every pocket, data volumes went vertical.
By 2010 global data generation was pegged at 2 zettabytes annually. By 2013 it had doubled to 4 zettabytes. By 2015 it had doubled again to 8 zettabytes. Sensing the hockey stick trend, IT experts began sounding warning bells about the limitations of conventional storage architecture designs and the looming exabyte-class data demands. Few heeded the call at first…until now.
Fast forward to today, and public cloud data storage services like Amazon S3, Microsoft Azure and Google Cloud hold unfathomable volumes of business and consumer data spread across hundreds of gargantuan server farms worldwide. The largest and most data-intensive public cloud providers are estimated to have a combined storage capacity exceeding 50 exabytes as of 2022 – and swelling by over 40% annually!
Meanwhile bewildering datasets from fields like astrophysics, genomics, molecular dynamics, financial modeling and autonomous transport are bringing even the most muscular traditional compute systems to their knees. For next-gen applications like detailed brain simulations, high-fidelity climate forecasting, AI neural architecture search and real-time full motion VR rendering, datasets spanning thousands of exabytes will be the norm.
Unorthodox Storage Problems Call for Unorthodox Solutions
While cloud data centers already toggle between tens of exabytes daily, their storage hardware architecture is built for commercial big data processing – not extreme cutting edge simulations or ultra high-resolution models pushing towards yottabytes (1024 exabytes!). That‘s why bleeding-edge data-centric supercomputing projects are getting creative with their storage schemes – repurposing everything from arrays of Blu-ray discs and magnetic tape reels to many-story tall robotic tape libraries.
The unprecedented appetite for ultra-high capacity storage from areas like cosmology, genetics, climatology, energy research and neuroscience is also birthing exotic new entrants like automated underground exabyte warehouses, hydrogen-fused storage crystals, synthetic DNA-based archives, volumetric optical storage media, atomic-scale memory devices, and of course, good old fashioned punchcards!
Jokes aside, as humankind keeps doubling down on its inexorable digitization and datafication, tools like deep learning and causality analytics will amplify the hunger for extreme-scale datasets even further. Forget terabytes – in many industries exabytes are already table stakes, zettabytes lie just around the corner, and the march towards yottabytes and beyond is already underway!
