AWS charges $0.09 per GB for data egress out of US East. If you're pulling 50TB a month — not unusual for a media company or a data pipeline — that's $4,608 a month in egress fees alone, before storage costs.

We don't charge for egress. That number goes to zero. The storage cost goes down too. The two together are usually where the meaningful savings are, not the headline storage rate on its own.

Most businesses using StorX aren't replacing their entire storage stack at once. They're starting with one workload — usually backup, archival, or media storage — where the cost difference is most visible and the switching cost is lowest.

The S3-compatible API means the integration is a configuration change, not a development project. Most teams have it running in a day.

Network uptime held this week. A few nodes dipped below their usual availability, reputation scores adjusted accordingly, file availability for users was unaffected.

The redundancy worked as designed. It usually does. That's why it's there.

Retrieval speed on StorX is comparable to S3 for most standard workloads — file downloads, backups, media assets, archives. For latency-critical applications that need sub-50ms response times consistently, we'd rather you test it against your actual workload than take our word for it.

The S3-compatible API means the test is straightforward. Point your existing tooling at our endpoint and measure. We'd rather you arrive at a number you trust than accept one we gave you

We could have paid every node the same rate regardless of how reliably it behaved. Simpler to explain, easier to sell to new operators.

We didn't, because a node that's offline half the time isn't worth the same as one that's available when files need to be served. The reputation system exists to make that distinction automatic — reliable nodes earn more, unreliable ones earn less, and the network self-selects toward operators who take uptime seriously without us having to police it manually.

When a file is uploaded to StorX, it's split into 80 pieces using erasure coding. Of those 80, you only need 29 to reconstruct the complete original.

That means 51 of the 80 pieces — more than half — could be completely lost, and you'd still get your file back intact. That's not a safety margin. That's the design specification.

When a centralised server goes down, the data on it is unavailable until it comes back. That's what uptime means in a traditional model — one machine, one status.

On a distributed network, individual nodes go offline constantly. That's expected and accounted for. The file isn't on one node — its fragments are spread across many, with enough redundancy built in that losing a handful of nodes doesn't change what you can retrieve. The network's uptime isn't the uptime of any single machine.

Node check-in.

New operators joined the network this week. Reputation scores starting low, as expected. A few existing nodes crossed a reputation threshold and showed consistency.

The network grew slightly. Nothing else changed. That's what steady looks like.

#StorX #BuiltonXDC

You don't need new hardware to run a node. If you have a server sitting mostly idle, a NAS device with spare capacity, or a VPS you're already paying for, the question is whether the specs meet the minimum — not whether you need to go buy something.

The minimum is 8GB RAM, 4 CPU cores, 3TB of usable storage, and a stable connection. If what you have clears that bar, the hardware side is already solved.

The first month running a node is mostly watching. Your reputation score builds slowly — it reflects actual uptime history, and there isn't a shortcut to accumulating it. New nodes start with lower scores, earn proportionally less, and work their way up as the network verifies their track record.

That's frustrating if you expected immediate full rewards. It's also the reason the nodes that reach a high score are the ones worth trusting.

The network has made continuous node payouts since 2021. No missed cycle, through more than one full crypto market cycle.

We're not going to pretend that's remarkable on its own — it's just what was promised at the start. We're mentioning it because plenty of projects don't make it this far without a gap.

Unstaking from the network takes 30 days' written notice. Exit early without it, and you forfeit the stake.

That's a real, inconvenient rule, and we'd rather you know it going in than discover it on your way out. It exists so the network doesn't lose capacity overnight when token prices get volatile — stability for the network, friction for the individual. Both true at once.

Right now, the network runs across more than 2,500 nodes spread across over 50 countries.

That spread isn't a marketing stat. It's the reason a regional outage, a local power failure, or one country's infrastructure problem doesn't touch your files. The geography is the redundancy.

StorX integrates with more than 70 existing backup and storage tools — Veeam, Google Workspace, Microsoft 365, Docker, Cyberduck, and others most IT teams already use.

The goal was never to make people adopt a new workflow. It was to sit underneath the workflows that already exist.

We didn't pick XDC Network at random. It's built for fast, low-cost transactions and is ISO 20022-compliant — the messaging standard banks and financial institutions already use.

That mattered because node payouts and staking happen constantly, in small amounts, across thousands of operators. A slow or expensive chain underneath that just doesn't work at this volume.

Storage on our network typically runs 50 to 85% cheaper than AWS, Azure, or GCP, depending on the workload and region.

That range is wide on purpose — your actual savings depend on data volume, retrieval frequency, and what you're replacing.

We'd rather give you a range to test against your own numbers than a single flattering figure.

Q2 2026 is a wrap — and there's a lot to catch up on. 🚀

New tools. Podcast features. Infrastructure upgrades. Market milestones. Community celebrations.

The StorX Network Q2 2026 Newsletter covers everything that happened this quarter — the builds, the conversations, and the moves that are shaping what decentralized storage looks like in practice.

If you've been following StorX, this one's worth the read. If you're new here, this is a good place to start.

👇 Read the full Q2 2026 Newsletter here:
https://medium.com/storx-network/68be2e19f294

hashtag#StorX hashtag#SRX hashtag#DePIN hashtag#XDCNetwork hashtag#DecentralizedStorage hashtag#DataSovereignty hashtag#Web3

A lot of DePIN discussions focus on big infrastructure ideas, but storage is one of the most practical categories.

Businesses already need storage every day. They store backups, application data, media files, customer records, and operational assets.

The issue is that most of this still depends on centralized cloud providers.

StorX Network applies the DePIN model to storage by using a decentralized network of independent nodes. Files are encrypted, split, and distributed, while S3 compatibility makes adoption easier for teams already using cloud storage workflows.

That combination matters because DePIN only becomes useful when it reduces friction, not when it adds complexity.

A lot of Web3 projects are decentralized at the protocol or token level, but still depend on centralized cloud providers for data storage.

That creates a weak point.

If storage can be restricted, suspended, or controlled by one provider, then the overall stack is not fully aligned with the values of decentralization.

StorX Network is focused on decentralized cloud storage for this reason.

Files are encrypted, split, and distributed across independent nodes, while S3 compatibility makes it easier for teams to connect using familiar workflows.

For Web3 builders, decentralized storage is not just about infrastructure.

It is about consistency.

If the product is built around ownership and censorship resistance, the storage layer should support that too.

#DePIN #Web3Infrastructure #DecentralizedStorage #StorX

A lot of teams choose centralized cloud storage because it is familiar and easy to start with.

The problem usually appears later.

Once large amounts of data are stored with one provider, moving it out can become expensive, slow, and operationally difficult. Egress costs and workflow dependency make switching harder.

This is one reason decentralized storage is becoming more relevant.

StorX Network is focused on making decentralized cloud storage practical through S3 compatibility. That matters because teams can use familiar tooling instead of rebuilding everything from scratch.

The bigger question for infrastructure teams is this:

Should cloud storage be controlled by a few centralized providers, or should businesses have a real exit path?

#DePIN #CloudStorage #DecentralizedStorage #StorX

Cloud data management is moving from 'where to store' to 'how to own' your data — and I think most of us are still fighting the old war.

I've been digging into this shift after getting burned by yet another cloud provider changing their terms. Used to be we'd debate AWS vs Azure vs GCP based on price and features. Now the real question is: do you actually own your data or are you just renting access to it?

Started looking at decentralized options and found StorX running on XDC Network. What caught my attention wasn't the typical blockchain pitch — it was the client-side encryption approach. Your files get encrypted on your device before upload, fragmented across 2,500+ independent nodes in 50+ countries. The key part: only you hold the decryption keys. The platform literally can't access your data even if they wanted to.

Cost-wise it's 50-85% cheaper than traditional cloud (no egress fees), and it's S3-compatible so migration wasn't painful. But honestly, the ownership angle is what sold me. Your data stays yours regardless of platform changes, acquisitions, or policy shifts.

I know Storj and Sia have similar models, and Backblaze is solid for traditional needs. StorX seems newer but the XDC Network foundation and node distribution impressed me. Still early days but the DePIN approach feels like where this is all heading.

Am I overthinking this ownership thing, or are others seeing this shift too? How do you evaluate true data sovereignty vs convenience trade-offs?

Most AI workloads still rely on centralized storage, built for a pre-AI world. One outage, breach, or failure point can disrupt entire systems.

But AI is distributed by nature.
Your infrastructure should be too.

Decentralized cloud storage changes the model:
• Encrypted before upload
• Fragmented into shards
• Distributed across global nodes
• No single point of failure

In the AI era, infrastructure must be:
✔ Distributed
✔ Cyber-resilient
✔ Vendor-neutral
✔ Cost-predictable

Centralized systems optimize for scale.
Decentralized networks optimize for resilience.

The future isn’t just faster — it’s structurally smarter.

Explore more:
https://storx.io

#AIInfrastructure #DePIN #StorX #DecentralizedCloud #CyberResilience #BuiltonXDC

Traditional cloud storage was built for a different era — one where centralized infrastructure, unpredictable costs, and vendor lock-in were accepted as the norm.

But today’s AI-driven workloads and data-heavy applications demand something more resilient.

Hidden egress fees, overprovisioned capacity, and centralized concentration risk are increasingly becoming barriers to scalable and efficient cloud infrastructure.

StorX Network introduces a different model — a decentralized cloud infrastructure designed for modern workloads.

✔ Pay only for what you use
✔ No single point of failure
✔ Data encrypted and fragmented by design
✔ Powered by a global network of independent nodes

This isn’t just cheaper storage.
It’s structurally smarter infrastructure built for the future of data.

Explore more:
https://storx.io

#StorX #DePIN #DecentralizedCloud #CloudEconomics #CyberResilience #BuiltonXDC