A New Cloud Storage Tier?

When you are paying around $10–$20 per GB per month for the fastest in-memory cache layer in the cloud, $0.015 per GB per month for Nearline object storage might seem cheap as chips. But as anyone managing petabyte-scale storage estates knows, the older and colder the data becomes, the less frequently accessed it is, the more sensitive cloud storage economics become.

Unlike expensive NVMe or DRAM, which lose data when powered off, cold data is persistent. Because cloud archive data is often measured in petabytes (PBs) rather than gigabytes, costs mount quickly. Even at a fraction of a cent per GB, storing multiple petabytes over many years becomes a strategic cost centre. Add retrieval costs, egress fees, air-conditioning, power for spinning disks, and operational management, and what looks cheap on paper can balloon in practice.

S3 to Cold Cloud Storage

As data ages, organisations weigh up two priorities: minimising cost and maintaining accessibility. Hyperscaler deep-archive tiers (e.g., Amazon Glacier Deep Archive or Azure Archive) are often positioned as the cheapest cloud option, at as little as $0.001 per GB. But these tiers are typically used for insurance backups, data not expected to be touched again, because retrieving anything substantial can be slow, operationally awkward, and surprisingly costly. In short, hyperscaler deep cold archive storage offerings are not designed to serve up production data.

The reality is that production data doesn’t vanish after its “hot” phase. Old production datasets, scientific experiments, digital media assets, compliance records, clinical archives, or AI training datasets may only be accessed occasionally; however, when needed, fast access without punitive egress fees is essential.

As Gartner noted in a 2023 report on cloud storage economics, “egress and retrieval charges remain a significant source of unplanned expenditure, often exceeding initial storage budgets for archival data projects” (Gartner, 2023).

So organisations typically store infrequently accessed production data on the HDD-based nearline storage tier rather than the environmentally friendly, lower-cost cold storage tier.

Real-World Use Cases

Media & Entertainment: Studios like A+E Networks generate petabytes of broadcast content each year. Archiving to hyperscaler storage may be cost-effective short term, but production demands quick access to old footage for remastering or licensing. As A+E’s CTO once said: “Access is everything… we don’t just want to store our content, we want to monetise it later” (Broadcast Tech, 2022).

Research & Academia: CERN produces over a petabyte of physics data every day. Much of this must be archived, but scientists still need fast retrieval for future analysis. In such environments, retrieval penalties aren’t just financial but can slow discovery (CERN Annual Report).

Healthcare & Life Sciences: Hospitals are required to retain patient imaging data for decades. A 2022 study in Applied Radiology highlighted how rising retrieval costs made AI-driven diagnostic model training prohibitively expensive for some institutions.

Financial Services: Compliance regulations often require firms to retain records for 7–10 years. A major European bank noted in 2021: “Our cloud storage costs tripled in three years, largely due to retrieval fees during audits” (The Banker).

AI & ML: AI training pipelines often handle terabytes to petabytes of historical data—from medical images to AI-generated datasets. Traditional hyperscaler archive storage incurs not only lengthy restore delays but also substantial egress costs, making experimentation, iterative model retraining and inference workloads expensive. (arXiv).

These industries highlight a shared pain point: long-term data retention with unpredictable retrieval costs if data is archived.

The On-Premises Parallel

Solutions such as Spectra Logic BlackPearl pioneered on-premises nearline S3 interfaces to complex high-capacity cold storage. Enterprises can store petabytes of production data with object storage, low-cost archive back-end infrastructure, simply storing data with little to no power requirements, all accessible via S3-like APIs, but crucially without retrieval fees. For some organisations, this on-premises model still makes perfect sense.

The barrier, however, has always been scale and skills. High upfront hardware costs, ongoing technology refreshes, and shrinking pools of storage administrators mean these complex systems are out of reach for many mid-sized and scaling organisations.

Cloud Cold Storage Becomes Nearline

Cloud Storage Providers are now challenging this status quo by offering the same enterprise-grade complex cloud cold object-based storage with a simple, seamless nearline S3 user experience and characteristics in the cloud:

• $0.0015 per GB per month storage costs, comparable to deep archive pricing.

• Access to streamed data in minutes, without rehydration delays.

• No egress or retrieval fees, removing the budget shock of restores.

For example:

• Wasabi offers hot cloud storage at around $7 per TB per month, chosen by organisations like the Boston Red Sox to manage historical video and analytics data (Wasabi Case Study).

• Customers like Verizon Media leverage Backblaze B2 Cloud Storage to handle large-scale nearline workloads at predictable costs (Backblaze Customers).

• CloudColdStorage stores data at deep archive prices and then streams that data back in minutes without expensive fees.

This allows IT teams to design data pipelines where:

• Active workloads stay on high-performance SSD/NVMe.

• Nearline low latency data moves to non-hyperscaler cloud storage (~$7 per TB) with hot storage performance.

• Cold production archives shift to more efficient cloud cold storage (~$1.55 per TB), without any restore penalties.

The result: significant long-term savings and greater predictability across multi-tier cloud storage strategies.

Store older production data for cents and use less energy retaining it.

The Numbers at Petabyte Scale

Here’s how costs stack up over 10 years for a 1 PB dataset:

• Hyperscaler block general-purpose SSD-based low ms latency hot storage: $22,800,000 (plus egress fees)

• Hyperscaler Nearline storage: $1,800,000 (plus egress fees and retrieval fees of around $1M per year to retrieve 1PB)

• Hyperscaler Deep Archive storage: $120,000 to $300,000 (plus retrieval and egress fees of around $6M per year to retrieve 1PB)

• Non-hyperscaler hot storage: $840,000 (limited or no egress fees or api calls)

• Cloud cold storage: $186,000 (no retrieval or egress fees)

At this scale, avoiding unpredictable retrieval charges is as impactful as reducing raw $/GB pricing.

Summary

• Cloud archive vs nearline is no longer a binary choice. Emerging cloud storage tiers blur the line by combining archive pricing with nearline access.

• Egress and retrieval fees are the silent budget killer; eliminating them is as important as lowering storage rates.

• Industries like healthcare, finance, media, and research all need affordable, predictable long-term storage that still enables access for compliance, monetisation, and AI training datasets.

Next Steps

1. Audit Your Data Estate: Identify how much of your current “hot” data actually needs to be kept spinning with no latency. You might be surprised at how much data can be kept cooler.

2. Model Retrieval Patterns: Estimate retrieval demand over 3–5 years; this is where hidden costs emerge.

3. Compare Cloud Archive vs Nearline Providers: Assess hyperscaler storage tiers alongside alternatives like Wasabi, Backblaze and CloudColdStorage.

4. Factor in AI and Analytics Growth: Retrieval demands are rising, not falling.

5. Run a Pilot: Benchmark access speeds, costs, and API compatibility before committing at scale.

Conclusion

The economics of cloud storage are shifting. What was once “deep archive only” is becoming viable for nearline production data. By adopting cloud cold storage with no egress or restore penalties, organisations can finally align long-term data strategy with predictable budgets.

Whether it’s a hospital safeguarding decades of scans, a studio monetising its film library, or a research lab mining historic datasets for AI, the ability to store at deep archive prices and retrieve at nearline speeds is a genuine new tier in the storage landscape, one that could redefine cloud storage economics over the next decade.

🎄 Be Prepared: Why Christmas Stocking and Cloud Storage Have More in Common Than You Think

The sun might be shining now, but Christmas is already on the horizon — just 120 sleeps away. As the Scouts say: “Be prepared.”

For many businesses, preparing for Christmas starts months in advance. A small retailer might not have the buying power of a supermarket chain, but still needs to stay competitive. A restaurant owner might prefer to focus on perfecting a festive menu rather than trawling the internet for decorations. That’s where wholesalers step in. They’ve already managed the supply chain, filled their warehouses, and made it easy for members to stock up at trade prices.

The same logic applies to data. Companies are producing and storing more of it than ever, knowing it may be needed again — sometimes in less than 120 days. But rather than sink time and money into managing infrastructure, most would rather focus on what they do best: creating brilliant content, innovating with research, or serving their own customers. Just like retailers lean on wholesalers, businesses lean on cloud providers to handle the heavy lifting of data storage and management.

But here’s the thing: The dominant wholesaler Costco may already have Christmas trees on display (see pic), but it isn’t the only one. According to IBISWorld, the UK has around 4,000 grocery businesses. A Chinese restaurant in the South East, for instance, might prefer SeeWoo over Costco for its festive menu. Different wholesalers meet different needs.

The same is true in the cloud. AWS, GCP, Azure, and IBM Cloud are household names — the Costcos of the digital world. They’re great for scalable compute and general-purpose storage. But they’re not always the best fit. ElasticSearch has a sharper solution for data analysis. Wasabi focuses on hot cloud storage at lower cost. And at CloudColdStorage, we specialise in super-low-cost, long-term data archiving.

You don’t have to wait 120 days for data to chill either. Data that’s just 30 days old can be actively archived with us — and streamed back in minutes — cutting cloud costs dramatically.

At just £1.16 per TB, you’ll even have budget left over for the Christmas party.

So whether you’re prepping your shelves or your servers, don’t limit yourself to just one “Costco” of the cloud. Explore the full marketplace.

✨ Merry Christmas from all of us at CloudColdStorage

Data increasing energy bills!

71 TWh of extra electricity required just to power future data centres

This intriguing BBC News article highlights concerns about rising energy bills due to the construction of power-hungry data centres, adding up to 71 TWh of electricity demand!

https://www.bbc.co.uk/news/articles/clyr9nx0jrzo

New data centres are being built, while existing ones, that are just a few years old, now have costly but empty floorspace. This is partly due to power restrictions imposed by local electricity boards, which limit the power available for older data centres to deploy more compute in the vacated shelves of older equipment.

These not-so-old data centres may quickly become obsolete.

Yet, there might be a surprisingly simple and quite obvious solution to reuse that empty floor space: data storage! Specifically, cold data storage. With all the focus on AI and computation, many in the industry are not considering data and how it should be correctly stored, even though data and vast amounts of it are critical for LLMs.

Once data is created, it is quickly moved to storage - something most people are familiar with from their home computers. Similarly, when data is stored in the cloud, it is staged on different tiers or classes of storage device depending on its age. Unfortunately, some cloud-based services and applications only consider the 'hot' storage tiers. We are now running out of power to support the unnecessary demands of these services. Added to that, the storage technologies available today won’t be able to keep up with the data demands of the next couple of years. New technologies like HoloMem are coming online, but they will be of no use if data is not directed to them.

It is time for more developers to adopt cold storage, so that 71 TWh of energy is not wasted spinning hard disks or cooling them.

By utilising cold storage services such as Cloud Cold Storage, slightly older data can be stored efficiently in the cloud. This service uses 97% less electricity than storing data on hard disks and restores data quicker than hyperscaler archive offerings without the retrieval and egress fees. As the service uses so little power to store so much data, data centre floor space can be utilised to store PBs of data in rackspace and aisles that are currently empty!

As more applications and online services adopt efficient data lifecycle tiering, including cold data storage tiers, then a higher percentage of data centre energy consumption can be dedicated and focused on compute rather than wasted spinning disks that hold data that is rarely accessed.

If you’re engineering data workflows, you can start saving budget, freeing up hot storage capacity and reducing energy consumption right now, start using CloudColdStorage for free today without entering credit card details and with no tie-ins.

Cool your data, use less power.

Tackling storage and budget pressures in media & entertainment workflows

From streaming blockbusters to immersive VR experiences, media production today is defined by unprecedented data demands. As projects scale in ambition and complexity, storage emerges as both a cornerstone and a cost pressure point across the industry.  Keeping pace with the data deluge introduces persistent challenges around cost, accessibility, and long-term usability. In production workflows, storage management becomes both a financial and logistical battleground.

The M&E mega-trends shaping cost and data storage landscapes

1. Explosive Data Growth in the Zettabyte Era

Global data production continues to surge. At the time of writing, we now have around 175 zettabytes of data circulating globally. For the M&E sector, this translates into storing, managing, and retrieving ever-larger media files while balancing speed, resiliency, and cost.

2. Ultra-High resolution, Immersive formats, & streaming expansion

The shift to 4K, 8K, VR/AR, and other high-definition formats is driving exponential storage growth. Meanwhile, streaming platforms continue to proliferate, each maintaining vast on-demand libraries, adding both scale and complexity to media storage infrastructures.

3. Hybrid storage architectures & automation

The prevailing trend is toward simplistic, flexible, hybrid storage models, blending on-premises, cloud, and cold tiers to optimise costs, accessibility, and performance. Orchestration systems now manage access, latency, and expenses in real-time, especially crucial for live production media workflows.

4. “Doing Less with Less”: Streamlined workflows & intelligent automation

As spotlighted at this year's NAB Show, the industry’s new mantra is simplicity: eliminate unnecessary steps, standardise workflows, and embrace AI-driven automation, so it is not just to do more, but to do less more efficiently.

5. Consolidation, monetisation, & AI-driven efficiencies

Broadcasters are consolidating operations for cost leverage, aided by generative AI tools for tagging, compliance, and content monetisation. Meanwhile, streaming platforms are moving into a profitability phase, bundling services and focusing on sports and mature franchises to increase margins.

Storage challenges in production

• The CAPEX vs. OPEX dilemma

Whether investing in on-site high-speed storage SAN/NAS, RAID arrays, or on-prem disk pools that offer the throughput essential for editing and transcoding workflows, these systems come with steep capital overheads: hardware provisioning, power, cooling, maintenance, and scale-up limitations; or optimising for a simpler fully managed storage as a service and paying ongoing cloud fees. High-performance and long-term workflows remain a financial burden, especially for mid-sized studios.

• Hidden cloud costs, egress & recovery fees

Hyperscale platforms can lure studios in with low per-GB storage costs, but unwelcome surprises in the guise of inflationary retrieval and egress fees often surface later when media sets are requested.

• On-prem data longevity & digital preservation

Owning storage media, whether drive, flash, or tape, requires lifecycle planning, format migration, and redundancy strategies to ensure access over many years. This process requires additional skills, management, and cost. Utilising an online cold storage service reduces the effort needed and provides data management and access long into the future.

• Discoverability & metadata gaps

Without effective metadata tagging and access tools, archives become opaque, undermining potential reuse, monetisation, or compliance.

Solutions that add long-term value

• Tiered storage with intelligent lifecycle management

Adopt fast tiers for active projects, simplify tiered access, and reducing the length of time before you tier down to cold storage as content ages, and automate transitions to minimise manual effort and cost with media management in between.

• Incorporate MAM/DAM tools

These offer web-based archive, backup, and metadata workflows that support on-premise disk, tape, or large long-term cloud repositories, providing automated and user-friendly solutions. Metadata-rich MAM features, such as customisable fields, previews, searchable proxies, cloning, encryption, and off-site storage management, are critical for long-term accessibility and preservation.

• Orchestration in hybrid workflows

Manage both on-site and cloud workflows seamlessly, particularly for live or peak workloads, using orchestration systems that automatically allocate resources, monitor performance, ensure security, and scale efficiently.

• For long-term storage, select providers that avoid recovery/egress fees.

New archival services from the likes of CloudColdStorage.com will save budgets over the short and long term because they are price-optimised for lower-cost storage tiers, preventing surprise restore charges as they utilise technology specifically chosen for its long-term storage credentials over millisecond access. A cloud-based cold storage service should be considered as part of a broader, diversified data storage strategy.

• Automate and simplify workflows

Use AI-assisted automation to prune redundant processes, generate metadata on ingestion, and ensure you store less, but smarter.

Next steps for media organisations

1. Assess your data footprint & storage model

Map current spending across active, nearline, and archival tiers—identify egress costs, duplication, and archival gaps.

2. Plan hybrid tiers with lifecycle automation

Define new policies (e.g., rather than wait 90 days “after 30 days inactive → cold tier”) and implement tools that trigger these transitions automatically.

3. Implement robust MAM/DAM systems

Prioritise MAM solutions for metadata-rich, search-friendly archiving, or integrate AI-enhanced DAM platforms when scale demands.

4. Use orchestration for peak and live workflows

Dynamically match compute/storage needs to production demand using orchestration systems, thereby reducing wasted capacity and spend.

5. Future-proof through metadata and AI

Ensure that stored assets are discoverable, accessible, and monetizable, both today and in the years to come, by embedding metadata generation and searchability at the start.

By understanding mega-trends—like the zettabyte explosion, immersive content, hybrid workflows, and AI-driven automation—media organisations can transform storage from a cost sink into a long-term asset. Starting with tiered storage that includes a cloud-based cold storage without egress fees, metadata-rich archiving, and smart orchestration, you build a resilient infrastructure that supports cost control, efficiency, and future reuse.

Archiving doesn't have to be a horror story.

Introducing Cloud Cold Storage, affordable, accessible, air‑gapped archiving made easy 🧊

We’re excited to announce the launch of Cloud Cold Storage (CCS), a friction‑free, ultra‑low‑cost archival service built for safeguarding your data long‑term, without restore delays or hidden fees.

🔍 Why it’s different

• Dedicated media per customer or workload

  Unlike traditional hyperscale archive platforms, where your data is sliced across pooled media, each Cloud Cold Storage customer gets their dedicated storage media. That means when you request your data, the system reactivates only your media, not a conglomerate of drives. That translates into rapid retrievals: terabytes of data streamed back in minutes rather than days.

• No egress or restore fees

  Unlike many archive services, which charge for retrieval or data transfer, Cloud Cold Storage offers this service for free. You pay only for storage, and if you ever need your data back, the download is entirely fee-free.

• Rock‑bottom pricing

  At just $1.55 per TB per month (roughly $0.00155/GB/month), CCS undercuts primary cloud archive offerings. Plus, there’s a free 14‑day trial with no credit card required.

• Eco‑friendly air‑gap storage

  Because your data sits offline until needed, CCS dramatically reduces power and cooling overhead. That not only cuts costs, but also shrinks the carbon footprint of your archive data.

🎯 Perfect for…

Whether you’re managing vast research datasets, AI/ML training archives, video surveillance repositories, healthcare records, or media and entertainment assets, CCS offers seamless access to that data:

• Research & Education: Ideal for institutions dealing with genomics data, scientific archives, or digital preservation. Integrated S3 Glacier‑compatible APIs mean you can plug into existing workflows and enjoy fast retrieval without surprise charges.

• Media & Entertainment: Store dormant or legacy projects ready to monetise and extract value in the future, without waiting on slow restores or paying egress fees.

• Healthcare & compliance: Archive sensitive records with air‑gapped security and predictable costs, without the need to manage on-premise systems.

🚀 Getting started is simple

Ready to archive?

1. Sign up for a no‑credit‑card trial, just your email, and you’ll be set up in minutes.

2. Upload via standard Amazon S3 Glacier interface.

3. When you need to retrieve data, expect high‑speed streaming, usually in just a few minutes, with no extra charges.

🕰️ What are you waiting for?

For anyone who values trustworthy, long-term data preservation without complexity or budget risk, this is archival reimagined.

Want to see how it works in your workflow? Try it free today, or get in touch—we’d love to help plan your long‑haul archive.

Preserving Science: The case for scalable, sustainable cloud based data archiving

In an era of data-intensive science, we are facing a quiet but growing crisis: how to sustainably preserve the sheer volume of data produced by modern research, while ensuring it remains accessible, verifiable, and usable for future generations.

Whether it’s genomics, climate modelling, particle physics, or AI training sets, scientific workflows are generating petabytes of data, often at speeds outpacing our capacity to store, curate, and retrieve them meaningfully. As data volumes grow, so too does the risk of digital obsolescence, fragmented access, excessive power usage and prohibitive storage costs.

The imperative for low-cost, long-term scientific data storage

High-value research data cannot be treated as disposable. Institutions like Cambridge University Press and members of the Digital Preservation Coalition recognise that scientific knowledge is a cultural asset, and digital preservation is fundamental to scholarly continuity. Yet traditional cloud storage models are often cost-prohibitive for long-term retention, especially when retrieval fees and unpredictable egress costs are factored in.

Scientific institutions need archiving solutions that:

• Are cost-effective enough to scale with exponential data growth.

• Provide independent, verifiable storage with transparent metadata and integrity guarantees.

• Allow easy and timely retrieval, not only for the data producers but also for external collaborators, auditors, and future researchers.

Bridging infrastructure and stewardship: a new model for research storage

Platforms like Cloud Cold Storage are increasingly relevant in hybrid data infrastructures, where active AI and high-performance computing workloads coexist with vast, infrequently accessed datasets. Digital Realty’s AI-ready architectures emphasise the need for tiered data strategies—optimising hot storage for real-time inference while offloading reference datasets, training, or audit logs to low-cost cold storage layers. This approach not only ensures performance but also dramatically reduces energy and operational costs.

At the same time, organisations such as Arkivum highlight the importance of policy-driven, compliant data stewardship throughout the data lifecycle, and Cambridge University Library has a blueprint for an open-source data repository for searchable research data. Arkivum advocate for digital archiving aligned with FAIR principles, ensuring that data remains Findable, Accessible, Interoperable, and Reusable, while adhering to strict regulatory frameworks such as GDPR, GxP, and HIPAA. This becomes particularly critical in sectors like healthcare, higher education, and pharmaceutical research, where data integrity, provenance, and chain of custody must be verifiable years or even decades after collection. This post by the University of Cambridge Library discusses how to embed scalable preservation activities into everyday workflows with no specialist DP required in an open environment that is inclusive with research data accessible to all.

These approaches signal a growing convergence between infrastructure efficiency and responsible data curation: hybrid architectures underpinned by cold storage provide the technical foundation, while governance frameworks, such as those supported by Arkivum, provide the operational assurance. For scientific institutions seeking both scalability and sustainability, this model represents a compelling blueprint for a long-term research data strategy.

Preservation is no longer optional

Scientific rigour demands reproducibility. But reproducibility depends on access, not only to published findings but to the underlying data itself. As preservation responsibilities shift from short-term research projects to long-term institutional strategy, infrastructure must adapt. The tools and platforms used to store this data must be transparent, affordable, and compatible with how science is done today and tomorrow.

What next?

As research institutions, data architects, and funders consider their long-term preservation strategies, the conversation must evolve beyond simple backups or “just-in-case” storage. We must treat archival storage as a foundational layer of scientific infrastructure.

To explore emerging models of scientific data preservation, including low-cost cold storage with guaranteed access, visit CloudColdStorage.com/research.

Ensure the science produced today can be verified, built upon, and trusted in the decades to come.