walrus

朋友，你是不是也这样：在短视频平台熬夜剪片，播放量几十万，收益却少得可怜；在写作平台日更，粉丝涨了，但文章版权和你没关系，平台说下架就下架。你感觉自己像个数字时代的“佃农”，在别人的土地上辛勤耕作，收成的大头却被平台拿走了。
问题出在哪儿？出在“数据在哪，权利就在哪”这个死结上。你的内容存在平台服务器里，你有的只是一个随时可被注销的“租客”账户。平台用你的内容吸引流量、赚取广告，甚至训练AI，而你除了那点微薄的流量分成或打赏，对这份数字资产几乎没有真正的控制权和所有权。
Walrus想干一件事：帮你“数字确权”，让你从“佃农”变“地主”。@Walrus 🦭/acc $WAL #walrus
它提供的不是另一个内容发布平台，而是一套属于你自己的数字资产仓库和自动化销售系统。你可以这样想象：
把作品存进自己的“数字金库”：你创作的4K高清原片、无损音乐母带、文章手稿，不再上传到平台服务器，而是作为加密的“Blob”存到Walrus网络。这东西从法律和技术上，都更像你名下的一处数字房产。给金库大门装上智能锁：你可以用智能合约，为这个作品设定任何你想要的规则。比如：“试看前3分钟免费，观看全片支付10元”；“允许转载，但每转载一次自动分我1元”；“本视频仅限持有我粉丝NFT的1000人观看”。规则由代码执行，没有中间商能篡改或克扣。让作品自己去“上班”赚钱：一旦设置好，你的作品就成了一件“活”的、能自动产生收益的数字资产。它可以同时出现在多个展示前端（各种App或网站），但无论在哪被消费，钱都会根据你预设的规则，直接、自动地打入你的钱包。
这对创作者意味着什么？
意味着你终于可以和平台谈判，而不是祈求。你可以对平台说：“我的内容在我的Walrus仓库里。你可以展示它来吸引用户，但每展示一次、每产生一次消费，请根据我的智能合约自动分账。否则，我就授权给别的平台。” 你的创作变成了一种可随时撤回、条件清晰的授权合作，而非无偿奉献。
当然，这条路刚开始，还很粗糙。用户体验、流量获取、粉丝迁移都是大难题。但它第一次提供了一套完整的技术方案，把“创作者主权”从口号变成了可运行的代码。它不一定能立刻让你暴富，但它给了你一个选择：是继续在别人的花园里当优秀园丁，还是去开垦一片真正属于自己的土地？ 对于那些受够了平台剥削、拥有核心粉丝的创作者来说，这可能是一次值得尝试的“数字出走”。

💾 Approfondimento sul settore dello storage: solido come un cane anziano FIL vs strategia audace WAL
1️⃣ Chi è il leader? Senza dubbio Filecoin (FIL)
Posizione: assoluto dominatore.
Fossato: reale capacità di storage fisico + enorme ecosistema generico.
Caratteristica: il “fondo indice” del settore dello storage. Acquistarlo significa acquistare la crescita media dell'intero settore, stabile ma difficile da moltiplicare per cento.
2️⃣ Chi è il jolly? Walrus ($WAL )
Strategia: non affrontare direttamente FIL, ma adottare una “guerra speciale”.
Arma principale: storage privato + nativo dell'ecosistema Sui.
Caratteristica: “azione in crescita” nel settore di nicchia. Alto rischio, grande volatilità, ma una volta realizzato (esplosione di Sui o necessità di privacy), le probabilità sono estremamente alte.

Alright, most people talk about blockchains, but very few talk about data, even though data is literally everything. This is exactly where @walrusprotocol steps in. Walrus isn’t trying to be the loudest project in the room — it’s trying to be one of the most useful. The idea is simple but powerful: decentralized, scalable, and efficient data storage that actually works for real-world applications. No fluff, no overcomplication, just solid infrastructure that Web3 desperately needs.

Walrus focuses on decentralized data availability and storage
Built to support scalable applications without bottlenecks
$WAL plays a key role in incentives and network participation
Designed with developers in mind, not just speculators
Long-term vision over short-term hype

If Web3 is going to grow up, projects like Walrus are essential. While many protocols fight for attention, @Walrus 🦭/acc is quietly solving one of the hardest problems in the space: how to store and access data in a decentralized way without sacrificing performance. The $WAL token ties the ecosystem together and aligns incentives for users and builders alike. Keep Walrus on your radar — infrastructure might not be flashy, but it’s what everything else depends on. #walrus

咱们在这个圈子里看多了“公链大战”，今天以太坊要分片，明天 Solana 要升级，各家都在为了 TPS（每秒交易量）争得面红耳赤，仿佛只要速度够快就能统治世界。但如果我们把视角拉高一点，会发现这些争斗多少有点“为了造车而忽略修路”的意味；因为无论结算层跑得有多快，所有的公链目前都面临着一个共同的、且越来越致命的隐疾——“数据臃肿”。所有的链都在试图把账本（Ledger）和数据（Data）混在一起存，这就像是非要把图书馆里的几百万本书全都塞进银行那个寸土寸金的保险柜里一样，既昂贵又愚蠢。而 Walrus (WAL) 现在的站位之所以让我觉得充满了战略智慧，是因为它压根没想去参选什么“公链之王”，它要做的是那个服务于所有国王的“通用大后方”。
你得明白，区块链的本质是一个极度昂贵的去信任状态机，它的强项是记账（谁拥有什么），而不是存储（具体是什么）。现在的尴尬在于，以太坊上的状态数据已经膨胀到了普通节点根本跑不动的地步，而 Walrus 提供了一种极具前瞻性的解题思路：“让上帝的归上帝，凯撒的归凯撒”。在这个架构里，高价值的资产确权依然留在以太坊或 Solana 的主网上，但那些占据了 99% 空间的图片、视频、前端代码以及元数据，统统卸载到 Walrus 这个无视链种差别的“中立存储层”里。这不仅仅是简单的外包，它实际上是在构建整个 Web3 行业的“统一数据湖”；无论你是来自 EVM 生态的开发者，还是 Move 系的拥趸，Walrus 都是那个可以无缝接入、且成本几乎可以忽略不计的“无限硬盘”。
这种“跨链数据组合性”的想象空间是巨大的。试想一下，未来的一款链游，它的核心资产（比如一把神剑）的 NFT 甚至可以跨链流动——今天它在以太坊上被交易，明天通过桥跨到了 Solana 上，但无论这个资产的“所有权指针”怎么变，它背后所指向的那个 3D 模型文件始终安稳地躺在 Walrus 的同一个 Blob 地址里，无需迁移，也无需复制。Walrus 在这里扮演的角色，就像是互联网世界里的 TCP/IP 协议，它打通了不同公链之间的“生殖隔离”，让数据内容本身成为了一种独立于链存在、却又能被所有链调用的公共资源。当数据不再依附于某一条特定的链而存在时，我们才算真正走出了“数据孤岛”的 Web2 陷阱。
而且，Walrus 能扛起这面大旗，靠的不是情怀，而是它那令人咋舌的性能指标。以前我们不敢提“全链存储”，是因为 Arweave 这种老前辈虽然理念好，但读写速度慢得像拨号上网，根本没法支撑高频交互。但 Walrus 依托于 Sui 的并行架构和独特的纠删码技术，硬是把去中心化存储的读写速度拉到了能跟 Web2 云服务掰手腕的级别。这意味着，Walrus 不仅能存“死数据”（文档、档案），更能存“活数据”（游戏状态、社交动态）；它让那些原本因为性能瓶颈而不敢上链的业务，第一次有了“去中心化”的可选项。
这种架构上的革新，最终会倒逼所有的公链向“瘦客户端”进化。未来的区块链主网将变得极度轻量化，它们只负责处理最核心的哈希验证和资产交割，而那庞大的、丰富多彩的数字世界实体，将由 Walrus 这样的基础设施来承载。这或许才是 Web3 最终极的形态：一个由无数条“瘦链”编织而成的信任网络，底下铺垫着 Walrus 这块厚实、廉价且永不丢失的“数据大陆”。所以，当大家还在为哪个 L1 的币价涨跌焦虑时，不妨多看看 Walrus，因为它正在铺设的，是承载整个加密文明重量的地基。

@Walrus 🦭/acc $WAL #walrus

Ho recentemente notato qualcosa. Il tricheco continua a comparire nelle conversazioni che non hanno nulla a che fare con l'hype, il prezzo del token o le narrazioni a breve termine. Appare quando i team parlano di dati che devono effettivamente durare. Di solito è un buon segnale. Molta infrastruttura Web3 viene testata in ambienti dove i dati sono temporanei e gli errori sono facili da ignorare. I sistemi di trading possono tollerare registri persi. Le prime app possono sopravvivere a link rotti. Ma non è lì che si costruisce la fiducia. La fiducia viene testata quando i dati devono essere disponibili mesi o anni dopo, e quando perderli non è un'opzione. È lì che

high authenticity, integrity, auditability and availability – all this
at a reasonable cost and low complexity.
Approaches to Decentralized Storage
Protocols for decentralized storage generally fall into two main
categories. The first category includes systems with full replication,
with Filecoin [30] and Arweave [46] serving as prominent examples.
The main advantage of these systems is the complete availability
of the blob on the storage nodes, which allows for easy access and
seamless migration if a storage node goes offline. This setup enables
a permissionless environment since storage nodes do not need to
rely on each other for file recovery. However, the reliability of these
systems hinges on the robustness of the selected storage nodes.
For instance, assuming a classic 1/3 static adversary model and an
infinite pool of candidate storage nodes, achieving “twelve nines” of
security – meaning a probability of less than 10−12 of losing access
to a file – requires storing more than 25 copies on the network3
.
This results in a 25x storage overhead. A further challenge arises
from Sybil attacks [16], where malicious actors can pretend to store
multiple copies of a file, undermining the system’s integrity.
The second category of decentralized storage services [23] uses
Reed-Solomon (RS) encoding [32]. RS encoding reduces replication
requirements significantly. For example, in a system similar to
blockchain operations, with 𝑛 nodes, of which 1/3 may be malicious,
and in an asynchronous network, RS encoding can achieve sufficient
security with the equivalent of just 3x storage overhead. This is
possible since RS encoding splits a file into smaller pieces, that we
call slivers, each representing a fraction of the original file. Any set
of slivers greater in total size to the original file can be decoded
back into the original file.
However, an issue with erasure coding arises when a storage
node goes offline, and needs to be replaced by another. Unlike fully
replicated systems, where data can simply be copied from one node
to another, RS-encoded systems require that all existing storage
nodes send their slivers to the substitute node. The substitute can
then recover the lost sliver, but this process results in 𝑂(|blob|)
data being transmitted across the network. Frequent recoveries can
erode the storage savings achieved through reduced replication,
which means that these systems need a low churn of storage nodes
and hence be less permisionless.
Regardless of the replication protocol, all existing decentral-
ized storage systems face an additional challenges: the need for a
continuous stream of challenges to ensure that storage nodes are
incentivized to retain the data and do not discard it. This is crucial
in an open, decentralized system that offers payments for storage
and goes beyond the honest/malicious setting. Current solutions
always assume that the network is synchronous such that the ad-
versary cannot read any missing data from honest nodes and reply
to challenges in time.
Introducing Walrus
We introduce Walrus, a new approach to decentralized blob storage.
It follows the erasure codes type of architecture in order to scale
to 100s of storage nodes providing high resilience at a low storage
overhead. At the heart of Walrus, lies a new encoding protocol,
3The chance that all 25 storage nodes are adversarial and delete the file is 3
−25 =
1.18 × 10−12
.
called Red Stuff that uses a novel two-dimensional (2D) encoding
algorithm that is self-healing. Specificaly, it enables the recovery
of lost slivers using bandwidth proportional to the amount of lost
data (𝑂(
|blob|
𝑛
) in our case). Moreover, Red Stuff incorporates
authenticated data structures to defend against malicious clients,
ensuring that the data stored and retrieved remains consistent.
One unique feature of Red Stuff is its ability to work in an
asychronous network while supporting storage challenges, making
it the first of its kind. This is only possible thanks to the two-
dimensional encoding that allows for different encoding thresholds
per dimension. The low-threshold dimension can be used from
nodes that did not get the symbols during the write flow to recover
what they missed, whereas the high-threshold dimension can be
used for the read flow to prevent the adversary from slowing down
honest nodes during challenge periods and collecting sufficient
information to reply to challenges.
One final challenge for Walrus, and in general, any encoding-
based decentralized storage system is operating securely across
epochs each managed by a different committee of storage nodes.
This is challenging because we want to ensure uninterrupted avail-
ability to both read and write blobs during the naturally occurring
churn of a permissionless system, but if we keep writing data in the
nodes about to depart, they keep needing to transfer them to the
nodes that are replacing them. This creates a race for the resources
of those nodes, which will either stop accepting writes or fail to ever
transfer responsibility. Walrus deals with this through its novel
multi-stage epoch change protocol that naturally fits the principles
of decentralized storage systems.
In summary, we make the following contributions:
• We define the problem of Asynchronous Complete Data-Sharing
and propose Red Stuff, the first protocol to solve it efficiently
even under Byzantine Faults (Section 3)
• We present Walrus, the first permissionless decentralized stor-
age protocol designed for low replication cost and the ability to
efficiently recover lost data due to faults or participant churn
(Section 4).
• We show how Walrus leverages Red Stuff to implement the
first asynchronous challenge protocol (Section 4.6)
• We provide a production-ready implementation of Walrus and
deploy a public testnet of Walrus. We then measure its perfor-
mance and scalability in a real environment (Section 7).
2 Models and Definitions
Walrus relies on the following assumptions.
Cryptographic assumptions. Throughout the paper, we useℎ𝑎𝑠ℎ()
to denote a collision resistant hash function. We also assume the
existence of secure digital signatures and binding commitments.
Network and adversarial assumptions. Walrus runs in epochs,
each with a static set of storage nodes. At the end of the epoch
𝑛 = 3𝑓 + 1 storage nodes are elected as part of the the storage
committee of the epoch and each one controls a storage shard such
that a malicious adversary can control up to 𝑓 of them.
The corrupted nodes can deviate arbitrarily from the protocol.
The remaining nodes are honest and strictly adhere to the protocol.
If a node controlled by the adversary at epoch 𝑒 is not a part of the Walrus: An Efficient Decentralized Storage Network
Table 1: Comparing Replication Algorithms
Replication for 10−12 Security Write/Read Cost Single Shard Recovery Cost Asychronous Challenges
Replication 25x 𝑂(𝑛|𝑏𝑙𝑜𝑏|) 𝑂(|𝑏𝑙𝑜𝑏|) Unsupported
Classic ECC 3x 𝑂(|𝑏𝑙𝑜𝑏|) 𝑂(|𝑏𝑙𝑜𝑏|) Unsupported
RedStuff 4.5x 𝑂(|𝑏𝑙𝑜𝑏|) 𝑂(
|𝑏𝑙𝑜𝑏 |
𝑛
) Supported
storage node set at epoch 𝑒 + 1 then the adversary can adapt and
compromise a different node at epoch 𝑒 + 1 after the epoch change
has completed.
We assume every pair of honest nodes has access to a reliable
and authenticated channel. The network is asynchronous, so the
adversary can arbitrarily delay or reorder messages between honest
nodes, but must eventually deliver every message unless the epoch
ends first. If the epoch ends then the messages can be dropped.
Our goal is not only to provide a secure decentralized system
but to also detect and punish any storage node that does not hold
the data that it is assigned. This is a standard additional assumption
for dencentralized storage system to make sure that honest parties
cannot be covertly compromised forever.
Erasure codes. As part of Walrus, we propose Asynchronous
Complete Data Storage (ACDS) that uses an erasure coding scheme.
While not necessary for the core parts of the protocol, we also
assume that the encoding scheme is systematic for some of our
optimizations, meaning that the source symbols of the encoding
scheme also appear as part of its output symbols.
Let Encode(𝐵, 𝑡, 𝑛) be the encoding algorithm. Its output are 𝑛
symbols such that any 𝑡 can be used to reconstruct 𝐵. This happens
by first splitting 𝐵 into 𝑡 symbols of size 𝑂(
|𝐵|
𝑡
) which are called
source symbols. These are then expanded by generating 𝑛 −𝑡 repair
symbols for a total of 𝑛 output symbols. On the decoding side,
anyone can call Decode(𝑇 , 𝑡, 𝑛) where𝑇 is a set of at least𝑡 correctly
encoded symbols, and it returns the blob 𝐵.
Blockchain substrate. Walrus uses an external blockchain as
a black box for all control operations that happen on Walrus. A
blockchain protocol can be abstracted as a computational black
box that accepts a concurrent set of transactions, each with an
input message 𝑇𝑥 (𝑀) and outputs a total order of updates to be
applied on the state 𝑅𝑒𝑠(𝑠𝑒𝑞,𝑈 ). We assume that the blockchain
does not deviate from this abstract and does not censor 𝑇𝑥 (𝑀)
indefinitely. Any high-performance modern SMR protocol satisfies
these requirements, in our implementation we use Sui [8] and have
implemented critical Walrus coordination protocols in the Move
smart contract language [7].
3 Asynchronous Complete Data Storage (ACDS)
We first define the problem of Complete Data Storage in a dis-
tributed system, and describe our solution for an asynchronous
network which we refer to as Asynchronous Complete Data Stor-
age (ACDS). Secondly, we show its correctness and complexity.
3.1 Problem Statement
In a nutshell a Complete Data Storage protocol allows a writer to
write a blob to a network of storage nodes (Write Completeness),
and then ensures that any reader can read it despite some failures
and byzantine behaviour amongst storage nodes (Validity); and
read it consistently, despite a potentially byzantine writer (Read
Consistency). More formally:
Definition 1 (Complete Data Storage). Given a network of 𝑛 = 3𝑓 +1
nodes, where up to 𝑓 are byzantine, let 𝐵 be a blob that a writer 𝑊
wants to store within the network, and share it with a set of readers
𝑅. A protocol for Complete Data Storage guarantees three properties:
• Write Completeness: If a writer𝑊 is honest, then every honest node
holding a commitment to blob 𝐵 eventually holds a part 𝑝 (derived
from 𝐵), such that 𝐵 can be recovered from O

|𝐵|
|𝑝 |

parts.
• Read Consistency: Two honest readers, 𝑅1 and 𝑅2, reading a suc-
cessfully written blob 𝐵 either both succeed and return 𝐵 or both
return ⊥.
• Validity: If an honest writer𝑊 successfully writes 𝐵, then an honest
reader 𝑅 holding a commitment to 𝐵 can successfully read 𝐵.
We present the ACDS protocols in a context where the storage
node set is fixed and static. And in subsequent sections describing
its use within Walrus, we discuss how it is adapted to allow for
churn into the committees of storage nodes.
3.2 Strawman Design
In this section, we iterate first through two strawman designs and
discuss their inefficiencies.
Strawman I: Full Replication. The simplest protocol uses full
replication in the spirit of Filecoin [30] and Arweave [46]. The
writer𝑊 broadcasts its blob 𝐵 along with a binding commitment to
𝐵 (e.g., 𝐻𝐵 = ℎ𝑎𝑠ℎ(𝐵)), to all storage nodes and then waits to receive
𝑓 + 1 receipt acknowledgments. These acknowledgments form an
availability certificate which guarantees availability because at least
one acknowledgement comes from an honest node. The writer 𝑊
can publish this certificate on the blockchain, which ensures that it
is visible to every other honest node, who can then request a Read(𝐵)
successfully. This achieves Write Completeness since eventually
all honest nodes will hold blob 𝐵 locally. The rest of the properties
also hold trivially. Notice that the reader never reads ⊥.
Although the Full Replication protocol is simple, it requires the
writer to send an O (𝑛|𝐵|) amount of data on the network which is
also the total cost of storage. Additionally, if the network is asyn-
chronous, it can cost up to 𝑓 + 1 requests to guarantee a correct
replica is contacted, which would lead to O (𝑛|𝐵|) cost per recov-
ering storage node with a total cost of O (𝑛
2
|𝐵|) over the network.
Similarly, even a read can be very inefficient in asynchrony, as the
reader might need to send 𝑓 + 1 requests costing O (𝑛|𝐵|).
Strawman II: Encode & Share. To reduce the upfront data dissem-
ination cost, some distributed storage protocols such as Storj
@Walrus 🦭/acc #walrus $WAL

Decentralized storage systems have long struggled with a difficult balance; achieving strong security and availability without wasting massive amounts of storage or network bandwidth. Traditional approaches often rely on full replication, which is secure but extremely expensive, or basic erasure coding, which reduces storage costs but becomes inefficient and fragile when nodes frequently join or leave the network.

Walrus introduces a fundamentally better approach. It is a decentralized blob storage network designed to deliver high integrity, availability, and auditability while keeping overhead practical at scale. At its core is Red Stuff, a novel two-dimensional erasure coding scheme that achieves strong security with roughly a 4.5 times replication factor far lower than fully replicated systems while enabling efficient, self-healing recovery. Instead of re-downloading entire files when data is lost, Walrus recovers only what is missing, using bandwidth proportional to the lost portion rather than the full blob.

A key breakthrough is that Red Stuff supports storage challenges in asynchronous networks. This prevents adversaries from exploiting network delays to pretend they are storing data they do not actually hold a weakness in many existing systems. Walrus further strengthens reliability through a multi-stage epoch transition protocol that handles storage-node churn gracefully, ensuring uninterrupted reads and writes even as committees change.

Built with authenticated data structures and backed by real-world testing at scale, Walrus demonstrates that decentralized storage can be both secure and efficient. It provides a practical foundation for NFTs, rollups, decentralized applications, data provenance, and encrypted data workflows without the prohibitive costs that have held decentralized storage back.
@Walrus 🦭/acc $WAL #walrus

@Walrus 🦭/acc 协议最近在Sui生态里挺火的，但它到底是个啥？简单说它想解决一个老问题：怎么在区块链上便宜、安全又抗审查地存大文件。
我们知道传统云存储（比如 AWS、Google Cloud）虽然快又好用，但中心化、贵，还可能被审查。而早期去中心化存储方案（比如 IPFS + Filecoin）虽然理念好，但使用门槛高、检索慢、成本也不低。Walrus 的思路有点不一样，它不直接让用户“上传-付费-下载”，而是把文件切碎、编码、分发到网络节点，再通过 Sui 的高性能账本做协调和验证。
技术上Walrus 用了“擦除编码”，这其实不是新东西，RAID 磁盘阵列、分布式数据库都用过。原理是把一个文件切成n块，再生成m个冗余块，只要拿到其中任意k块就能还原原始文件。这样即使有些节点下线或作恶，数据也不会丢。同时它把实际的大文件存在链下（叫 blob 存储），只在 Sui 链上存验证信息和元数据，既省gas费又提升效率。
比如一个独立游戏开发者想发布一个2GB的游戏客户端。如果全塞进链上，光存储费就得破产；如果放中心化CDN，又担心哪天被下架。用Walrus，他可以把安装包上传，系统自动切片、加密、分发给全球志愿者节点（未来可能是激励节点）。玩家下载时，从多个节点并行拉取碎片，拼回完整文件，整个过程无需信任单一服务商，也几乎没人能单方面删掉这个文件。
那Walrus有啥优势？首先，成本低。Sui 本身交易便宜，加上数据不上链，长期存储费用远低于Arweave或Filecoin。其次，抗审查强。因为没有中心控制点，政府或公司很难强制删除内容。第三，和 Sui 深度集成。智能合约可以直接引用 Walrus的blob ID，实现“链上逻辑+链下数据”的无缝组合，这对 NFT、DID、去中心化社交应用特别有用。
但挑战也不少。第一，生态还小。现在节点主要是测试网志愿者，真要扛住大规模商用，得有经济激励模型，比如代币奖励或质押机制，目前还没完全落地。第二，检索速度依赖网络拓扑。如果节点分布不均，某些地区用户下载可能很慢。第三，隐私保护有限。虽然数据被切片加密，但如果上传的是公开内容，比如开源软件那没问题；但如果是敏感数据，还得额外加端到端加密，Walrus 本身不包办这个。
市场环境方面，Walrus目前算Sui的“官方存储层”，背靠Mysten Labs（Sui 的开发团队），资源和关注度都不缺。但它面对的对手不少，比如Filecoin 在通用去中心化存储领域已占先机；Arweave 主打“永久存储”；Even Storj、Sia这些老牌项目也在优化体验。Walrus 的机会在于“专精”，不做通用存储，而是深度服务Sui生态内的dApp，比如链上游戏存资源包、SocialFi 应用存帖子附件、DePIN 项目存传感器日志等。
长远看Walrus 如果能把激励模型跑通，让节点有利可图，同时保持低延迟和高可用性，很可能成为Sui上的“默认存储引擎”。就像以太坊有Swarm（虽然后来没成），Solana 有 Shadow Drive，每个高性能 L1 都需要一个匹配其速度和成本结构的存储方案。
总的来说Walrus不是革命性的新发明，而是务实的技术整合者。它没喊“颠覆云存储”的口号，而是先解决 Sui 开发者眼前的问题：如何便宜、可靠地存大文件。如果这条路走通了，或许真能成为 Web3 基础设施里那块沉默但关键的拼图。

¡Hola, hola, hola, hola! ¡Feliz y bendecido jueves, WALRUSFANS! Hoy, 29 de enero de 2026, el token Walrus (WAL) muestra un rendimiento mixto dentro del ecosistema Sui.

Aquí está el resumen actual:
Precio en tiempo real: WAL está valorado actualmente en aproximadamente 0.1202$.
Tendencia inmediata: En las últimas 24 horas, ha registrado un ligero aumento del 0.60 %. Sin embargo, la tendencia semanal se mantiene bajista, con una caída acumulada del 12.31 % en los últimos 7 días.
Actividad del mercado: El volumen de operaciones en las últimas 24 horas ronda los $7.47 millones de USD, lo que indica una liquidez activa.

Contexto de la red: Como pilar de la infraestructura de almacenamiento de la red Sui, su precio suele verse influenciado por la percepción general del ecosistema, que recientemente ha experimentado fluctuaciones debido a breves interrupciones operativas en su red principal. Análisis rápido: A corto plazo, el token parece estar buscando soporte tras la corrección semanal.

La predicción para este día sugiere una estabilización cerca del rango de $0.12 USD, a menos que el mercado de altcoins experimente una volatilidad externa significativa. Puedes monitorear los movimientos en tiempo real en Binance Square para conocer la opinión de la comunidad sobre su papel en el almacenamiento descentralizado.
@Walrus 🦭/acc 🙌🏼 #walrus 😃 $WAL 🪙

玩区块链的都知道一个潜规则：链上项目犯错不可怕，反正能改——合约升级、数据迁移、重新部署一套新系统，之前的错误就像没发生过。很多项目的成长史，说白了就是“不断推翻过去的自己”，链的作用只是把这个过程公开，却从没真正限制过这种“反复重来”。直到我深入了解Walrus，才突然意识到：原来链上系统也能被设计成“不能随便犯错”的样子，而这种“不宽容”，可能恰恰是未来复杂链上应用最需要的东西。
今天就用大白话跟大家唠透Walrus：它不是什么解决TPS、降低Gas费的“性能神器”，而是一套让链上系统“对历史负责”的“行为约束机制”。它没说不让你犯错，却通过一个简单的设计——让错误的痕迹永远无法被轻易抹去，彻底改变了链上项目的试错逻辑。这事儿听起来简单，却可能给区块链行业带来一场悄悄变革。
先搞懂：传统链上的“试错自由”，到底有多“随心所欲”？
在Walrus出现之前，绝大多数链上项目都在享受“试错自由”——说白了就是“犯错成本太低”。咱们举个常见的例子：
某DeFi项目刚上线时，智能合约的收益计算逻辑有漏洞，导致早期用户收益少发了。按传统玩法，项目方会怎么做？直接发布一个“V2版本”合约，把旧合约的资金迁移过去，旧合约废弃不用，之前的漏洞就像被“删掉”了；再比如某NFT项目，早期设计的元数据结构不合理，后面想加新属性，直接重新部署一个新合约，旧NFT要么销毁要么快照迁移，之前的不合理设计就被“掩盖”了。
更极端的是，有些项目半年内迭代了5个版本，每个版本都推翻之前的数据结构，最后连团队自己都记不清早期数据是怎么设计的。为啥大家敢这么“随心所欲”？因为传统链上存储就像一本“可以随时撕页、重写的草稿本”——你写的东西不算数了，直接撕了重写就行，没人会追究之前的错误。
这种模式在行业早期确实好用。区块链项目大多是摸着石头过河，没人知道正确方向是什么，“快速试错、快速迭代”能让项目尽快找到市场需求，活下来。但随着行业发展，问题越来越明显：
• 对用户来说，频繁迁移、升级可能导致资产丢失、交易记录混乱，比如某项目迁移合约时，部分用户的代币没及时转过去，旧合约废弃后资产直接归零；
• 对项目方来说，长期“甩锅式迭代”会让系统变得臃肿，不同版本的数据不兼容，后续开发要花大量时间处理历史遗留问题，越往后越难推进；
• 对机构来说，这种“没有历史责任感”的系统根本不敢用——你今天能随便改数据、删错误，明天我的资产上链了，你会不会因为一个错误就把整个历史推翻？
但大家都习惯了这种模式，没人觉得有问题，直到Walrus跳出来说：“链上的历史，不该被这么轻易对待。”
Walrus的核心魔法：不是禁止犯错，而是让错误“甩不掉”
Walrus到底做了什么？其实核心逻辑特别简单：它设计了一套“长期可恢复的数据结构”，简单说就是——一旦数据写进Walrus，就会被永久保留，而且未来的系统、第三方都能随时调取、引用这些历史数据。它没明文规定“不许犯错”，却通过这种设计，把错误的“代价”放大了、延长了。
我举个真实案例：有个接入Walrus的Web3工具类项目，早期团队没经验，每周都都要调整一次数据结构——比如周一觉得该记录用户的交易时间，周三觉得还要加交易地点，周五又觉得应该补充用户设备信息。三个月下来，系统里积累了18万条历史状态，其中30%都是早期实验阶段的“半成品数据”。
按传统玩法，他们早就把这些“半成品数据”删掉或迁移了，但在Walrus上，这些数据删不掉、也藏不住。更关键的是，后续开发新功能时，这些历史数据会“找上门来”：比如新功能要调用用户的交易记录，就必须兼容早期只记录了时间的旧数据；要统计全局数据，就必须解释清楚哪些是实验数据、哪些是正式数据。
这一下就给团队带来了“心理负担”：以前改数据是“拍脑袋就能干”，现在改之前要想清楚——这个改动会不会和历史数据冲突？未来会不会被新功能引用？要不要和社区达成共识？原本一周能上线的功能，现在要花两周讨论、测试，确保和所有历史数据兼容。
这种“负担”，正是Walrus的核心设计——它改变了“失败的代价结构”。在传统链上，失败的代价是“当下的一点麻烦”（比如用户投诉、重新部署），但在Walrus上，失败的代价是“长期的历史包袱”——你今天的一个小错误，会在未来的每一次开发、每一次升级中都提醒你“你曾经犯过这个错”。
这种改变，直接让团队的行为模式发生了变化：
• 写数据前，会更谨慎：不再是“先写进去再说，不行再改”，而是反复讨论“这个数据有没有必要写？格式对不对？未来会不会用到？”；
• 改逻辑前，会更严格：不再是“觉得不合理就推翻”，而是先想“能不能兼容历史数据？有没有更好的办法在不否定过去的前提下优化？”；
• 做决策前，会更民主：不再是团队内部拍板，而是会征求社区意见，因为一旦决策失误，这个错误会被永久记录，影响未来的每一个人。
我把这种变化总结为“从试错自由到责任约束”：Walrus不是不让你试错，而是让你在试错前想清楚——你能不能承担这个错误带来的长期后果？你愿不愿意为这个错误负责到底？
这和大多数“鼓励快速试错”的链上基础设施完全相反。很多项目把“快速失败”当成创新的前提，但他们忘了：当失败的痕迹被完整保留时，失败本身就会改变人的行为。就像我们小时候写作业，如果知道作业本不能撕、不能改，会写得更认真；如果知道写错了能随便涂掉，自然会更随意。

真实案例：被Walrus“约束”的项目，后来怎么样了？
Walrus的这种设计，不是万能的，对不同项目的影响天差地别。我观察了几个接入Walrus的项目，总结出了两种截然不同的结果：
正面案例：成熟团队的“如虎添翼”
有个做链上数据溯源的项目，团队已经有明确的产品方向，只是在细节上需要优化。接入Walrus后，他们的开发节奏明显变慢了——原本一周能上线的功能，现在要两周。但半年后再看，效果特别明显：
• 系统稳定性拉满：同期接入的其他项目，平均每两个月就会出现一次数据兼容问题，而他们半年内零故障；
• 历史数据复用率高：接近40%的早期数据还在被新功能直接调用，比如早期记录的商品溯源信息，现在结合AI分析，能生成更详细的供应链报告；
• 机构合作更顺利：因为数据可追溯、不可篡改，而且历史记录完整，他们顺利和两家传统企业达成了RWA上链合作——对方最看重的就是“系统能对历史负责”。
对成熟团队来说，Walrus的“约束”不是负担，而是“质量保障”。它让团队避免了很多不必要的试错，把精力集中在真正有价值的创新上，而且完整的历史数据本身就是一种资产，能衍生出更多新功能。
反面案例：探索期团队的“举步维艰”
还有个做社交类DApp的项目，处于早期探索阶段，产品方向还没定，今天想做链上聊天，明天想做NFT社交，后天又想加DAO治理。接入Walrus后，他们直接被“压垮”了：
• 每一次方向调整，都会留下一堆历史数据，后续想改方向，就要处理这些“包袱”——比如之前记录的聊天数据，和新的NFT社交功能不兼容，又不能删，只能花大量时间做适配；
• 团队成员越来越焦虑：“现在的每一次尝试，都会成为未来的负担”，导致决策越来越保守，最后干脆停更了；
• 半年后，项目宣布放弃Walrus，重新部署到普通公链上，虽然又回到了“快速试错”的模式，但之前积累的历史数据变成了“无用的垃圾”，白白浪费了时间和成本。
这也说明，Walrus不是适合所有项目的“万能药”。它更像是为“有明确方向、追求长期稳定”的项目准备的，而不是为“还在摸石头过河”的探索期项目准备的。
为什么现在需要Walrus？链上系统正在进入“复杂时代”
可能有人会问：“快速试错不好吗？为什么要搞这种‘约束型’基础设施？”答案很简单：区块链行业正在从“野蛮生长”进入“复杂时代”，以前的“试错自由”已经跟不上需求了。
早期的链上应用都很简单：比如比特币就是转账，以太坊早期就是发代币、简单借贷。这些应用逻辑单一，就算犯错，影响范围也小，改起来也容易。但现在不一样了：
• RWA上链越来越多：股票、债券、房地产这些现实资产被搬到链上，一个数据错误可能导致数百万甚至数亿的损失，根本不能随便试错；
• 复杂DeFi协议崛起：跨链借贷、合成资产、算法稳定币，这些协议涉及多层逻辑、多链交互，一个小漏洞可能引发连锁反应，而且错误很难追溯；
• 机构入场越来越深：传统金融机构开始布局区块链，他们对系统的稳定性、可追溯性、合规性要求极高，“能随便改历史”的系统，他们根本不敢用。
举个例子：某银行想把1亿美元的债券代币化上链，如果用传统公链，一旦合约有漏洞，或者数据记录错误，银行只能重新部署合约，这会引发投资者恐慌，甚至违反金融监管规则；但如果用Walrus，数据一旦写入就不能轻易篡改，而且所有历史记录都能追溯，银行能清楚地解释每一笔交易的来龙去脉，监管和投资者也会更放心。

这就是Walrus的价值：它不是在限制创新，而是在为“更复杂、更重要的创新”铺路。当链上应用的价值越来越高、影响范围越来越广时，“对历史负责”就不再是“可选项”，而是“必选项”。
Walrus的聪明之处在于，它没有用权限、审查或复杂的规则来“禁止犯错”——这些都会破坏区块链的开放性和去中心化。它用的是最公平、最无法规避的东西：时间。时间是最残酷的约束，它不会立刻惩罚你，但会在未来的每一次扩展中，提醒你曾经做过的选择。
Walrus把这种约束引入了链上数据层，让历史不再只是“被动存档”，而是“主动参与系统演化”的一部分。比如一个DeFi协议在Walrus上运行了三年，它的每一次参数调整、每一次逻辑优化、每一次错误修复，都会被完整记录下来，新功能可以基于这些历史数据做优化，监管可以基于这些历史数据做审计，用户可以基于这些历史数据做决策。
这种“让历史为未来赋能”的设计，远比单纯的“快速试错”更有长期价值。就像一个人，年轻时可以犯错，但如果能从错误中学习，并且对自己的行为负责，才能真正成长；如果每次犯错都想“抹去痕迹”，永远也长不大。链上系统也是一样，只有学会对历史负责，才能真正走向成熟。
@Walrus 🦭/acc #walrus $WAL