Acceldata Blows Past 0.5 Exabytes of Data Observed Monthly as Enterprise Data Observability Accelerates

When I joined Acceldata as Chief Product Officer two months ago, I did my due diligence on the capabilities of the #dataobservability platform. I verified its enterprise-readiness, as I had Ashwin Rajeeva CTO and co-founder walk me through the architecture that claimed to be infinitely scalable. But it's one thing to get a look under the hood, it's another to see it in running in action.

And with that I'm thrilled to convey that Acceldata has crossed a significant threshold of 0.5 exabytes observed monthly.

Now, while anything measured in exabytes is staggering, I'll detail comparisons in terms of petabytes in this article since the rest of the world still predominantly measures data in terabytes and petabytes. 0.5 exabytes is 500 petabytes.

So, what does 500 petabytes observed monthly mean as a milestone? And what does it mean for the largest Global 2000 enterprises that rely on the Acceldata platform every day?

Why Enterprises Trust Acceldata at near Exabyte-scale?

Enterprises want and need reliable, actionable data, it's fueling insights from analytics, meeting compliance reporting, and increasingly new #genai initiatives. They trust a platform that delivers robust monitoring capabilities to ensure that the data is accurate, consistent, and available when they need it. Companies such as Oracle , Dun & Bradstreet , PhonePe (India's division of Walmart and the #1 provider of mobile digital payments process $1 Trillion in transactions), Health Care Service Corporation , PubMatic , The Hershey Company , and others which are currently anonymized: including top 3 Telcos and 4 the US. Top 10 largest banks and credit card processors globally, the largest computer manufacturer in the world, and more. Read about their stories here.

Many are replacing legacy data quality tools in favor of "shifting left" to identify and resolve issues before they escalate, minimizing downtime and maximizing productivity.

Spend Intelligence and Compute Optimization adds Icing to the Cake

Beyond reliability, Enterprises also need to reduce costs. The fact that spend intelligence and compute optimization is part of the capabilities of Acceldata's Data Observability platform is found money for many. By providing insights into compute, data and tool usage like popular products such as Snowflake and Databricks means cost savings that companies can redirect to new initiatives. Significant cost savings without compromising on performance or reliability is the reason large enterprises are prioritizing enterprise data observability over many other initiatives.

Visualizing of 0.5 Exabytes or 500 Petabytes Observed Monthly

To grasp the enormity of 500 petabytes, consider this:

• In Physical Terms: Imagine 20 million four-drawer filing cabinets filled with text. Multiply that by 500, and you'd need 10 billion four-drawer filing cabinets.
• In Enterprise Terms: According to the latest estimates, 328.77 million terabytes of data are created each day. That's 120 zettabytes per year or 10 zettabytes per month, over half of that if not more are videos, emails and other forms of unstructured data. So 0.5 exabytes observed monthly is already a small but mighty slice of that pie, especially when you consider how much data is used on a daily basis by large enterprises.

The Data Landscape, Past and Future

• Back in July 2017, CERN announced that its data center had 200 PB archived in its tape library. We're observing more than 2.5x that amount every month.
• IDC predicted that by 2025, there will be 175 zettabytes -- or approximately 175,000,000 PB -- of data that needs storage. With the rise of the internet of things and big data analytics and AI, the data landscape is only going to get more massive, and we are here for it.

We're all Just Getting Started

As we celebrate this milestone of 0.5 exabytes observed monthly, we're looking at an incredible future for data observability at enterprise exabyte-scale. Given the rapid rate of new enterprises signing up for Acceldata, and the rapid pace of expanded use cases from our existing customers that are looking to cover their entire data landscape, we believe 1 exabyte won't be far away. We like everyone is just getting started with leveraging data, with a bright and promising future with #AI. Or as we like to say, we are "Accel"erating data reliability and compute optimization. Please visit our website at acceldata.io to learn how you can join the exabyte-scale party and benefit from data reliability and compute optimization today.

For reference: Table of data memory or storage units in descending and increasing size: From the Bit to the Quettabyte

• The Bit
• The Byte
• Kilobyte (1024 Bytes)
• Megabyte (1024 Kilobytes)
• Gigabyte (1,024 Megabytes, or 1,048,576 Kilobytes)
• Terabyte (1,024 Gigabytes)
• Petabyte (1,024 Terabytes, or 1,048,576 Gigabytes)
• Exabyte (1,024 Petabytes) <--- We are half way to an Exabyte
• Zettabyte (1,024 Exabytes)
• Yottabyte (1,024 Zettabytes, or 1,208,925,819,614,629,174,706,176 bytes)
• Ronnabyte (1,024 Yottabytes)
• Quettabyte (1,024 Ronnabytes)