The development of Web3 decentralized storage is evolving from mere 'data notarization' to 'data capitalization'. Traditional protocols, due to their rigid architecture, centralized governance, and single-function flaws, struggle to meet the programmable, high elasticity, and strong privacy demands of emerging scenarios such as AI large models, RWA assetization, and cross-chain collaboration for data storage. The Walrus Protocol, built on the Sui ecosystem, leverages three foundational innovations: data objectification core design, Red Stuff two-dimensional coding technology, and a decentralized governance system. It not only resolves the cost and scalability paradox of traditional storage but also upgrades storage from a 'basic service' to a 'composable value layer'. Through deep collaboration with Sui, it achieves the programmability of the entire lifecycle of data storage, management, circulation, and monetization, truly defining the next-generation paradigm of Web3 storage.
The most disruptive innovation of Walrus lies in integrating data objectification into the core logic of decentralized storage, which is the essential difference from protocols like IPFS and Filecoin. Traditional storage protocols treat data as indistinguishable byte streams, only implementing basic proof and retrieval functions. Data access rights, lifecycle management, and value flow depend on external smart contracts, creating barriers to cross-protocol compatibility. In contrast, Walrus, based on Sui's Move language object model, transforms every piece of stored data into a uniquely identifiable on-chain programmable object, granting data independent attributes, behaviors, and permission rules. Developers can directly set access policies for data objects through smart contracts, such as automatically unlocking NFT metadata at specific times, allowing AI training datasets to be open only to authorized nodes, dynamically updating RWA asset certificates based on on-chain events, and even enabling autonomous interaction between different data objects. This design transforms data from static storage files into programmable, combinable, and tradable on-chain assets, providing core infrastructure for emerging scenarios such as data DAOs, trusted AI, and decentralized content platforms. For example, the decentralized media platform Decrypt stores 4K video libraries in Walrus and implements automatic revenue distribution for playback earnings by writing copyright sharing contracts for each video object, achieving a 30-fold increase in efficiency compared to traditional solutions, which is precisely the scene innovation capability brought by data objectification.
Supporting the implementation of Walrus's data objectification is its Red Stuff two-dimensional encoding technology, which brings extreme cost and performance optimization and is the technical foundation for handling massive data storage demands. Traditional decentralized storage protocols, in order to ensure data reliability, either adopt full replication models, such as Arweave's 10-fold copy storage, or use traditional RS encoding, which incurs high data recovery costs and has excessive redundancy, resulting in Filecoin's annual storage costs reaching 200 USD/TB, while Arweave's permanent storage costs soar to 3500 USD/TB. In contrast, Walrus's Red Stuff encoding is innovatively designed based on fountain codes, segmenting data into tiny 'slices' and performing redundancy encoding in two dimensions, requiring only 4-5 times redundancy to achieve high availability, 'even if a third of the network nodes fail, data can still be fully restored.' Its annual storage cost is as low as 50 USD/TB, a 75% reduction compared to Filecoin and a staggering 98.6% reduction compared to Arweave, making decentralized storage competitive with centralized cloud services like AWS S3 for the first time. Additionally, the fast recovery feature of Red Stuff encoding allows for data reconstruction after node failures without large-scale data transfer, significantly reducing network bandwidth consumption, and, along with Sui's high-throughput consensus layer, achieves millisecond-level response for data uploads and retrievals. This dual breakthrough in cost and performance allows Walrus to handle large-scale data storage needs such as AI training datasets, high-definition rich media, and metaverse 3D models, becoming the core data foundation for the integration of AI and Web3.
If data objectification and Red Stuff encoding are the technical core of Walrus, then the decentralized governance system is the key to achieving scalable development while maintaining decentralized attributes, thoroughly solving the industry's problem of 'the larger the scale, the more serious the centralization' faced by traditional storage protocols. Most decentralized storage protocols, during their development, tend to form power monopolies due to large nodes accumulating more stakes, leading to network centralization. However, Walrus avoids this issue through a four-layer mechanism design: first, token delegation for distributed staking, allowing users to delegate WAL tokens to any independent node instead of concentrating stakes in a few large nodes, naturally achieving distributed allocation of staking rights; second, performance-oriented node rewards, where a node's WAL rewards are linked only to verifiable online time and data storage reliability rather than the scale of node staking, allowing small nodes to compete fairly with large nodes as long as they perform well, breaking the monopoly logic of 'scale equals advantage'; third, strict node punishment mechanisms, where a node that shows negligence, falsifies, or censors data will have its staked WAL tokens directly penalized, and frequent transfers of stakes will also be punished to prevent malicious entities from manipulating the network; fourth, collective governance of core parameters, where key decisions such as storage prices, the composition of the node committee, and protocol upgrades are voted on by all WAL token holders, ensuring decision-making power is always decentralized within the community. This governance design allows Walrus to maintain a decentralized structure with over 100 independent node operators while achieving a scale of over 800+ TB of encoded data and 14 million blobs, truly achieving 'scalability without centralization.'
The value of Walrus also lies in the flywheel effect formed by deep collaboration with the Sui ecosystem. The combination of the two constructs an integrated decentralized data system of 'consensus layer + storage layer,' becoming the core growth engine of the Sui ecosystem. Walrus is not an independent storage protocol from Sui; rather, it serves as the native data layer of the Sui ecosystem, reusing its mature infrastructure such as MoveVM, storage fund, and zkLogin, achieving seamless communication with the Sui chain. When users store data in Walrus, they only need to complete authorization through the Sui wallet, and the on-chain metadata and storage cost settlement are directly completed on Sui, significantly lowering the access threshold for developers and users; at the same time, the storage activities of Walrus will continuously consume SUI tokens as gas fees. It is estimated that if Walrus reaches a storage scale of 1EB, the annual consumption of SUI will reach 240 million tokens, accounting for 15% of the circulation, forming a positive flywheel of 'increasing storage demand → increasing SUI consumption → highlighting deflationary effects → enhancing ecological value.' Additionally, Sui's horizontal scalability and programmability provide underlying support for Walrus's data objectification, allowing the programmable rules of data to deeply integrate with DeFi, NFT, and GameFi applications on Sui. This ecological collaboration transforms Walrus from a single storage protocol into the core infrastructure for Sui to accommodate the next generation of Web3 applications, making Sui the first public chain ecosystem with a native programmable storage layer.
In 2026, Walrus further clarified its three development directions, continuously solidifying its position as a Web3 storage infrastructure: first, lowering the barrier to use, making it as simple for developers to use Walrus as using Web2 tools, and launching more user-friendly CLI tools and SDKs for seamless integration with mainstream development frameworks; second, strengthening default privacy, further upgrading Seal access control features, and building verifiable privacy data workflows to meet the strong privacy needs of DeFi and data markets; third, deeper integration with Sui to achieve seamless communication between blockchain and data layers, enabling data objects to directly invoke smart contracts and on-chain assets on Sui, unlocking more cross-layer collaboration scenarios. From the ecological landing perspective, Walrus has become the 'data hub' of the Sui ecosystem, hosting 37% of Sui NFT metadata and forming deep collaborations with projects like elizaOS, FLock.io, and LINE FRIENDS, covering diverse scenarios such as AI agent memory, distributed AI training, and Web3 gaming, and has also gained recognition from Grayscale for launching a dedicated trust, marking the entry of decentralized storage into the vision of traditional financial institutions.
Looking at the development of the Web3 storage track, from the early pure proof-of-storage needs to today's programmable, privacy-focused, and value-driven requirements, the core demands of the industry are undergoing a fundamental change. The emergence of Walrus is not just a simple technological iteration; it redefines the essence of storage through data objectification — storage is no longer a 'safe' for data but is the 'infrastructure' for the flow of data value. It achieves programmable storage through data objectification, balances cost and performance through Red Stuff encoding, realizes a win-win situation between scaling and decentralization through decentralized governance, and achieves an ecological flywheel effect through collaboration with Sui. In the context of massive data storage demands brought by AI large models and the penetration of Web3 into the real economy, the next-generation storage paradigm defined by Walrus is becoming the core link connecting data, assets, and applications, driving Web3 from 'asset on-chain' to 'data value on-chain.'
In the future, with the implementation of Walrus's 2026 technology roadmap, its privacy capabilities and ecological integration capabilities will be further upgraded, and the potential of data objectification will continue to be explored. In this era where data becomes the core means of production, Walrus not only builds a more efficient and secure storage foundation for Web3 but also allows users to truly grasp the ownership, management rights, and revenue rights of their data, laying a solid foundation for the development of a decentralized data economy.
