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Decentralized Storage vs Centralized Cloud for Video

AIOZ Network
7 min readSeptember 01, 2026
aioz-streamguide

Amazon can tell you exactly how durable your video files are on S3: a specific number, backed by a specific architecture, published on their own pricing page. Ask a decentralized storage network the same question and the answer is structurally different, not just a different number. That difference, not just "cheaper" or "more expensive," is the actual thing worth understanding before choosing between them for video.

TL;DR:

  • Amazon S3 states its durability directly: "designed to exceed 99.999999999% (11 nines)," achieved by replicating data across a minimum of 3 Availability Zones by default.
  • Decentralized storage networks achieve durability differently and don't agree on one method: Storj uses Reed-Solomon erasure coding (split into pieces, any subset reconstructs the file), Filecoin uses cryptographic Proof-of-Replication and Proof-of-Spacetime to continuously verify storage providers still hold the data.
  • "Immutable" and "durable" are not the same claim. A blockchain record proving content hasn't been tampered with says nothing about whether the actual video bytes are still retrievable if the nodes storing them go offline.
  • AIOZ Stream's own documentation doesn't publish a specific replication factor, erasure-coding scheme, or durability percentage, unlike AWS's explicit "11 nines" figure.
  • The real differentiator isn't a bigger durability number, it's not depending on one company's operational decisions and pricing changes for where your video lives.

How centralized storage proves durability

Amazon's own S3 documentation states the platform is "designed to exceed 99.999999999% (11 nines) data durability" and explains the mechanism directly: S3 "stores data redundantly across a minimum of 3 Availability Zones by default, providing built-in resilience against widespread disaster." That's a specific, auditable architectural claim, not a vague promise, three or more physically separate data centers each hold a copy, and AWS's own infrastructure and operational practices are what's actually being trusted to keep that redundancy intact. Customers can also choose single-AZ storage to save cost, or multi-region storage for stronger geographic resilience, but the default and the headline number both rest on the same foundation: one company controlling every copy, backed by a formal, published guarantee.

Server racks representing centralized cloud storage infrastructure

How decentralized storage proves durability, and why it isn't one method

Decentralized storage networks solve the same problem, keeping data available when any single node can disappear, but different networks solve it with genuinely different mechanisms, not a shared standard. Storj uses Reed-Solomon erasure coding: a file gets split and encoded into more pieces than are needed to reconstruct it, so a configuration like 16-of-32 (illustrative numbers from Storj's own documentation) needs only half the pieces to recover the original file, achieving comparable durability to 10x full-copy replication at roughly an eighth of the storage overhead. Filecoin takes a different, more cryptographic approach: Proof-of-Replication verifies at intake that a storage provider actually created and sealed a unique physical copy of specific data, and Proof-of-Spacetime then continuously re-verifies, on an ongoing schedule with real economic penalties for failure, that the provider still holds it and it's still retrievable. Where AWS asks you to trust its operational practices and a published SLA, Filecoin's model is designed so no single party has to be trusted, the proof itself is the guarantee, re-verified on a schedule rather than asserted once. A third distinct approach, the one IPFS is built around, doesn't center on a redundancy guarantee at all, it centers on content addressing: a file is identified by a hash of its own contents rather than a location, and a distributed hash table tracks which nodes currently hold a copy. That solves a different problem than Storj or Filecoin solve, verifying a file hasn't changed and finding wherever a copy currently exists, but on its own it doesn't guarantee a copy still exists anywhere at all; IPFS deployments typically pair content addressing with a separate pinning or replication layer to actually guarantee persistence, which is worth knowing before assuming "IPFS" alone answers the durability question the way S3's architecture does.

"Immutable" is not the same claim as "durable"

This distinction matters more than it might first appear, and it's an easy one to blur. AIOZ's own Web3-streaming documentation states that content uploaded to a Web3 streaming platform "is recorded on the blockchain, making it immutable and resistant to unauthorized alterations or removal." That's a real, true claim, and it's a different claim from durability. A blockchain record proves a piece of content existed and hasn't been tampered with, it's a tamper-evidence guarantee about a reference, not a redundancy guarantee about the actual video bytes sitting somewhere retrievable. Data can be perfectly "immutable" in the sense that its record can't be forged, while the underlying file becomes unrecoverable if every node that was actually storing those bytes goes offline with no replication mechanism to fall back on. Marketing language that leans on "blockchain-recorded, immutable" without separately addressing redundancy is answering a question the reader didn't ask.

What AIOZ Stream actually documents

Checked directly against AIOZ's own concepts and DePIN documentation: neither publishes a specific replication factor, an erasure-coding configuration, or a Filecoin-style continuous proof mechanism for how many independent copies of a given video actually exist across the network, or how that's verified over time. That's a real, specific gap relative to AWS's explicit "11 nines" figure or Storj's documented erasure-coding approach, not a criticism of whether AIOZ's storage works, just an honest statement about what is and isn't publicly specified. Treat "decentralized" and "durable" as related but separate claims here: the architecture is genuinely distributed across independent DePIN node operators, covered in more depth in the AIOZ DePIN article, but the specific redundancy math backing a durability number isn't something this research found published anywhere. For anyone weighing this against a documented alternative, the practical move is asking directly, through AIOZ's own support channels or dashboard documentation, rather than assuming either a Storj-style erasure-coding scheme or a Filecoin-style continuous proof mechanism sits underneath the platform by default.

The tradeoff that actually matters

Chasing a bigger durability number misses what's actually different here. AWS's 11 nines is a genuinely strong, well-earned figure, and a small team isn't going to out-engineer Amazon's redundancy architecture by going decentralized. What decentralized storage changes isn't the failure-rate math, it's who controls the failure modes that aren't about hardware at all: a pricing change, a policy update, an account suspension, a company's own business decisions about a service tier. Centralized storage concentrates that kind of risk in one company's hands along with the physical redundancy; decentralized storage spreads both the physical redundancy and that operational risk across a network no single party controls outright. Concretely: a video platform on S3 is one pricing-page update, one account-suspension decision, or one region's policy change away from a real operational disruption, regardless of how strong the underlying 11-nines durability is, because durability and dependency are separate axes and centralized storage only optimizes the first one by design. A platform spread across an independent operator network doesn't have that single point of business-level failure, even though, as covered above, it usually can't point to a figure as precise as AWS's to describe its physical redundancy. Whether that tradeoff is worth it depends on what a specific project is actually worried about, hardware failure or vendor dependency, and the cost side of that comparison (which routinely favors AIOZ's usage-based model for delivery specifically) is covered separately in the cost comparison article.

Frequently Asked Questions

What does "11 nines" of durability actually mean?
99.999999999% durability, per AWS's own S3 documentation, achieved by storing data redundantly across at least 3 Availability Zones by default rather than a single location.

Do all decentralized storage networks use the same redundancy method?
No. Storj uses Reed-Solomon erasure coding, splitting files into more pieces than needed for recovery; Filecoin uses cryptographic Proof-of-Replication and Proof-of-Spacetime to continuously verify storage providers still hold the data. These are genuinely different mechanisms, not variations on one standard.

Does blockchain immutability mean my video file can never be lost?
No. Immutability means the record of the content can't be tampered with, it says nothing about whether the actual file bytes remain retrievable if the nodes storing them go offline without a redundancy mechanism backing them up.

Does AIOZ Stream publish a specific durability percentage like AWS does?
Not that this research found. AIOZ's documentation doesn't specify a replication factor, erasure-coding scheme, or durability figure comparable to AWS's published "11 nines."

Is decentralized storage more durable than centralized cloud storage?
Not necessarily, and that's not really the right comparison. AWS's redundancy architecture is extremely strong and well-documented. Decentralized storage's real differentiator is distributing operational control and dependency risk, not out-engineering AWS's failure-rate math.

Why would someone choose decentralized storage if AWS's durability is so well-proven?
To avoid depending on one company's pricing, policy, and business decisions for where video data lives, a different kind of risk than hardware failure, covered from the cost angle in the linked cost-comparison article above.

References

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