Is the era of Petabytes Coming?

Is the era of Petabytes Coming?

IDC analysts predict that by 2025, global data growth will hit a mindblowing 175 zettabytes. Most of this data will be unstructured, and it will need to be properly protected.

Storage providers around the world have been receiving requests for solutions that can handle exabytes of data. Interestingly, these inquiries aren't just coming from hyperscalers. The tech race, driven by emails, documents, social media, and other materials, is creating an explosion of data. This shift is changing how businesses communicate and operate, producing massive amounts of unstructured data in companies and institutions.

Petabytes Are the New Normal

Smaller and medium-sized businesses are still working with terabytes of data. But larger companies are increasingly managing petabytes of data. Over half of large enterprises now handle at least 5 PB of data, with 80% of it being unstructured. Even more interesting, 89% of this data is stored in cloud environments—whether hybrid, public, or multi-cloud. The growth of data has been talked about for years, but the rapid pace is new. This acceleration is driven by technologies like the Internet of Things, High-Performance Computing, machine learning, and artificial intelligence.

The Challenges of Petabyte Data Protection

As data grows, protecting petabytes of information becomes a real challenge. Conventional backup systems, like those based on Network Data Management Protocol (NDMP), struggle to keep up at the petabyte scale. One issue is the time it takes to create full backups. This can take days—or even weeks—especially when the network is overloaded. NDMP, in particular, becomes slow and often fails with such large amounts of data. Another issue is the need to scan data before backing it up, which adds more complexity.

Backup Complexity at Scale

Incremental backups are a key optimization technique. But at the petabyte scale, identifying which files have been modified can take a lot of time and resources. On top of that, many companies, along with regulatory requirements, need to test their backups after they're created. This adds more days to the process.

For smaller companies managing tens of terabytes of data, the challenge is already significant. But as organizations approach petabyte-scale storage, the complexity grows. The pressure of quickly filling disks and tapes isn’t the only issue. Backup and disaster recovery (DR) requirements are also changing fast. IT is now central to almost every industry, and it’s no longer enough to just create and encrypt backups. Today, organizations are focused on:

  • Continuous data protection (CDP)
  • Security and Compliance
  • Bare-metal recovery (complete server recovery with operating systems, files, and configurations)
  • Shortening backup windows
  • Faster file recovery

Backups Under Scrutiny

Until recently, petabyte-scale backups were rare. But as data continues to grow—thanks to advanced analytics and AI modeling—the need for effective backup is more critical than ever. One trend that’s growing is the rise of smaller language models. These models are cheaper to run than large-scale systems like ChatGPT and Claude, and they can be deployed on local devices. However, they still need a lot of data to train effectively.

Backup remains the last line of defense against attacks, sabotage, or hardware failures. For massive data sets, even a small data loss can be disastrous. Fortunately, backup and DR tools are evolving. Some now offer insights into backup performance, capacity usage, and error trends. Predictive analytics powered by machine learning can help forecast storage needs and potential failures. Reporting dashboards provide a clear view of trends, compliance, and recovery planning.

Managing Growing Digital Assets

For companies with just a few terabytes of data, data management isn’t a top priority because the storage costs are low. However, as digital assets grow, so do the costs. The rise of unstructured data is prompting many organizations to take action. They want to reduce costs and improve information security.

Some companies have already started recognizing new needs in data management. In recent years, we've seen new product groups, like:

  • Data Security Posture Management (DSPM)
  • AI Enablement
  • Governance, Risk, and Compliance (GRC)

While these products are still niche, they’re expected to grow in importance over time.

The Art of Managing Data

Many businesses still struggle with basic data management questions, such as:

  • How many snapshots did you generate last year?
  • How many of them are still active in your environment?
  • When was the last time you accessed files created five years ago?

For organizations approaching the petabyte boundary, these questions will become more common. Answering them will help businesses see how much they can save by managing their data more efficiently. This isn’t just about spending less on new storage devices. It’s also about avoiding penalties from cyberattacks or regulatory non-compliance.

The first step in efficient data management is eliminating unnecessary data. This means cutting out bad practices that lead to data piling up. The next step is categorizing data based on its importance and how often it’s accessed. For example, some data can be moved to cheaper storage for six months. If it turns out to be accessed frequently, it can be moved back to faster, more efficient storage. Data that hasn't been accessed for long periods (e.g., 24 months, unless required for legal or regulatory reasons) can often be safely deleted.

Reducing Redundant Data

Another way to optimize storage is by reducing redundant data through deduplication and compression:

  • Deduplication: This process removes duplicate copies of data, reducing storage needs. There are two types: Inline deduplication (performed before data reaches the storage device) and Traditional deduplication (performed after data is stored)
  • Compression: This reduces file sizes. Compression can be: Lossless (ideal for critical business data)Lossy (used to reduce size by discarding some data)

For companies on a tight budget, managing backups for massive data sets is a big challenge. But with strategies like tiered storage, deduplication, and compression, companies can optimize both storage and backup costs.

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