Walrus is a decentralized data storage protocol built on the Sui Network, focusing on providing high-reliability, low-cost, and programmable large-scale storage solutions for AI, DeFi, blockchain games, and NFT applications.
Current decentralized storage faces several core issues: high data redundancy leading to elevated costs, limited retrieval efficiency, and a lack of deep integration with smart contracts. Walrus's positioning is clear — acting as an "on-chain verifiable and off-chain efficient storage" middleware, bridging the gaps of traditional storage solutions through this design.
From a technical perspective, Walrus adopts three key innovations: first, erasure coding technology, enabling a small number of nodes to recover complete data and significantly reducing storage costs; second, an epoch-based storage mechanism, naturally suited for long-term and high-frequency data needs; and third, native programmable storage capabilities, allowing data states to be directly referenced by smart contracts, which is especially friendly for AI and DeFi applications.
Why choose Sui? This is not simply an ecosystem port. Sui’s Object Model combined with a parallel execution architecture provides a foundation with high TPS and low latency, perfectly fitting large-scale data read/write operations. More importantly, this architecture offers genuine underlying support for the concept of "storage as an asset." In other words, Walrus effectively becomes the data infrastructure layer of the Sui ecosystem.
From the perspective of application potential, scenarios such as AI training data, DeFi contract interactions, and blockchain game state storage can all benefit from this solution. The cost optimization and verifiable features of decentralized storage precisely address the dual needs of data reliability and economic efficiency for these applications.
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Liquidated_Larry
· 01-11 07:15
The erasure coding method to reduce costs is indeed powerful, but how much cheaper it can actually run depends on the actual deployment... Sui has high TPS, which is great, but the concern is that storage might become the new bottleneck.
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VibesOverCharts
· 01-11 01:42
Walrus really seems to have solved the old problem, but I wonder if it actually works well in practice.
If it can truly reduce storage costs, the data burden on DeFi would be significantly lowered.
Sui's ecosystem builders are really getting serious about development, unlike some chains that just talk big.
The design of erasure coding is clever, but I'm worried about maintenance keeping up in the future.
It seems like AI training data is the most promising area; maybe I should jump in and scoop some up at the bottom.
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LightningClicker
· 01-08 07:53
Erasure coding should have been adopted long ago; the previous storage solutions were really inadequate.
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With Sui's parallel execution combined with this storage layer, does it feel like the ecosystem is now complete?
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Data storage for chain games has always been a pain point. If it can really run smoothly, could the costs be cut in half?
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I'm just worried it might be all talk and no action. Let's see how the mainnet performs.
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Native programmable storage is quite interesting; having contracts directly reference it makes things much easier.
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The Sui ecosystem is rapidly building infrastructure; this pace is quite aggressive.
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Once the cost issues are solved, DeFi should be able to innovate with new ideas.
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RugResistant
· 01-08 07:52
Erasure coding is indeed awesome. Can the cost be pushed this low? I'm thinking about running a node to give it a try.
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UnluckyValidator
· 01-08 07:43
Erasure coding can indeed save costs, but how do you ensure node stability?
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GetRichLeek
· 01-08 07:42
Reducing costs with erasure coding sounds good, but to be honest, whether the Sui ecosystem can really take off is still a question mark... I thought about these when I last bottomed out, but in the end, I still suffered a heavy loss.
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StillBuyingTheDip
· 01-08 07:29
Erasure coding sounds good, but how many projects can actually use it? It still depends on whether the Walrus team can successfully integrate the ecosystem.
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NoStopLossNut
· 01-08 07:28
Erasure coding sounds impressive, but can it really reduce costs that much? It still depends on how it performs in practice.
Walrus is a decentralized data storage protocol built on the Sui Network, focusing on providing high-reliability, low-cost, and programmable large-scale storage solutions for AI, DeFi, blockchain games, and NFT applications.
Current decentralized storage faces several core issues: high data redundancy leading to elevated costs, limited retrieval efficiency, and a lack of deep integration with smart contracts. Walrus's positioning is clear — acting as an "on-chain verifiable and off-chain efficient storage" middleware, bridging the gaps of traditional storage solutions through this design.
From a technical perspective, Walrus adopts three key innovations: first, erasure coding technology, enabling a small number of nodes to recover complete data and significantly reducing storage costs; second, an epoch-based storage mechanism, naturally suited for long-term and high-frequency data needs; and third, native programmable storage capabilities, allowing data states to be directly referenced by smart contracts, which is especially friendly for AI and DeFi applications.
Why choose Sui? This is not simply an ecosystem port. Sui’s Object Model combined with a parallel execution architecture provides a foundation with high TPS and low latency, perfectly fitting large-scale data read/write operations. More importantly, this architecture offers genuine underlying support for the concept of "storage as an asset." In other words, Walrus effectively becomes the data infrastructure layer of the Sui ecosystem.
From the perspective of application potential, scenarios such as AI training data, DeFi contract interactions, and blockchain game state storage can all benefit from this solution. The cost optimization and verifiable features of decentralized storage precisely address the dual needs of data reliability and economic efficiency for these applications.