This article provides an objective comparison of Walrus and Irys from a technical perspective across 6 dimensions.
**Written by: **Ponyo
Compiled by: Sui Network
Key Summary
🔧 Architecture: Irys is a fully functional integrated Layer 1 "Data Chain" that provides native blob access for contracts, but requires a brand new set of validation nodes. Walrus is an erasure-coded storage layer built on Sui, which is easier to integrate but requires cross-layer coordination.
💰 Economic Model: Irys adopts a single token IRYS to unify payment fees and rewards, simplifying user experience, but with higher price volatility risks. Walrus, on the other hand, divides functionality into two tokens: WAL (for storage) and SUI (for gas), effectively isolating costs, but requiring the maintenance of two incentive systems.
📦 Persistence and Computing Power: Irys maintains 10 full replicas and streams data directly into its virtual machine; Walrus, on the other hand, uses approximately 5 times redundancy with erasure coding and hash verification, resulting in lower storage costs per GB, but a more complex protocol implementation.
💾 Compatibility: Irys offers a "one-time payment, permanent storage" donation model, which is very suitable for storing immutable data, but has high upfront costs. Walrus, on the other hand, uses a "pay-as-you-go, automatic renewal" leasing mechanism, which facilitates cost control and can quickly integrate with Sui.
📈 Adoption Status: Walrus is still in the early stages but is developing rapidly, with PB-level storage, over 100 node operators, and has been adopted by several NFT and gaming brands. In contrast, Irys is still in the pre-expansion stage, with data volume not yet reaching PB level, and the node network is still growing.
Walrus and Irys are both committed to solving the same problem: providing reliable and incentivized on-chain data storage. However, their design philosophies are completely different: Irys is a Layer 1 blockchain specifically built for data storage, integrating storage, execution, and consensus into a vertically integrated architecture; whereas Walrus is a modular storage network that relies on Sui for coordination and settlement while operating an independent off-chain storage layer.
Although the Irys team initially portrayed it as a superior "built-in" solution compared to Walrus, which was defined as a limited "external" system, in reality, both have their strengths and weaknesses, with different trade-offs. This article provides an objective comparison of Walrus and Irys across six dimensions from a technical perspective, refuting one-sided conclusions and offering developers a clear selection guide to help them determine the most suitable path based on cost, complexity, and development experience.
1. Protocol Architecture
1.1 Irys: Vertically Integrated L1
Irys embodies the classic concept of "self-sufficiency." It comes with its own consensus mechanism, staking model, and execution virtual machine (IrysVM), all of which are tightly integrated with its storage subsystem.
The verification node simultaneously assumes three roles:
Store user data in complete copies;
Execute smart contract logic in IrysVM;
Protect the network security through a PoW + staking hybrid mechanism.
Since these functions coexist within the same protocol, every layer from the block header to the data retrieval rules can be optimized for large-scale data processing. Smart contracts can directly reference on-chain files, and storage proofs will follow the consensus path for ordering regular transactions. Its advantage lies in the high consistency of the architecture: developers only need to deal with a single trust boundary and a single fee asset (IRYS), and the experience of reading data in the contract code is akin to native support.
However, the cost of this is a higher startup cost. A brand new layer of network must recruit hardware operators from scratch, build indexers, launch block explorers, strengthen clients, and cultivate development tools. In the early stages, when the verification nodes have not yet grown, block time assurance and economic security lag behind established chains. Therefore, Irys's architecture opts for deeper data integration at the expense of ecological startup speed.
1.2 Walrus: Modular Stacking Layer
Walrus takes a completely different approach. Its storage nodes operate off-chain, while Sui's high-throughput L1 handles sorting, payments, and metadata through Move smart contracts. When a user uploads a blob (data block), Walrus shards it and distributes the storage across various nodes, then records an on-chain object on Sui that contains the content hash, shard allocation, and lease terms. Renewals, forfeitures, and rewards are executed as regular Sui transactions, paying gas with SUI, but using WAL tokens as the unit of settlement for storage economics.
Relying on Sui, Walrus immediately gains the following advantages:
Numerous existing Move developers can integrate directly without the need for protocol migration.
But the cost is the need for cross-layer coordination. Each lifecycle event (upload, renewal, deletion) must be coordinated between two semi-independent networks. Storage nodes must trust the finality of Sui while still maintaining performance during Sui congestion; meanwhile, Sui validator nodes do not verify whether the actual disk stores the data, so they must rely on Walrus's cryptographic proof system to ensure accountability. Compared to an integrated design, this architecture inevitably incurs higher latency, and some transaction fees (SUI gas) will flow to roles that do not actually store data.
1.3 Design Summary
Irys adopts a vertically integrated monolithic architecture, while Walrus is a horizontally layered modular solution. Irys has greater architectural freedom and a unified trust boundary but needs to overcome the ecological building challenges brought by cold starts. Walrus, on the other hand, leverages Sui's mature consensus system to significantly lower the access threshold for developers within the existing ecosystem, but must deal with the complex coordination between two economic domains and operator systems. There is no absolute superiority of either model; they simply have different optimization directions: one pursues coherence, while the other pursues composability.
When the choice of protocol depends on the developer's familiarity, ecological attractiveness, or launch speed, Walrus's layered model may be more practical. However, when the bottleneck lies in the coupling of deep data and computation, or when customized consensus logic is required, a chain like Irys, which is specifically designed for data, has sufficient reason to bear a heavier architectural burden.
2. Token Economics and Incentive Mechanisms
2.1 Irys: A token driving the entire protocol stack
The native token IRYS of Irys encompasses the economic model of the entire platform:
Storage fee: Users prepay IRYS to store data;
Execute gas: All smart contract calls are also priced in IRYS;
Miner Rewards: Block subsidies, storage proofs, and transaction fees are all paid in IRYS.
Since miners are responsible for both data storage and contract execution, computing income can compensate for the lack of storage revenue. Theoretically, when DeFi activities on Irys are robust, computing revenue will supplement data storage, thereby providing services at close to cost price; if contract traffic is low, the subsidy mechanism adjusts in reverse. This cross-subsidy mechanism helps to balance miner revenue and align the incentives of various roles within the protocol. For developers, a unified asset means fewer custody processes and a simplified user experience, particularly suitable for scenarios where users are not expected to interact with multiple tokens.
However, the downside is the risk correlation of single assets: once the price of IRYS drops, the rewards for computation and storage will decrease simultaneously, putting miners under dual pressure. The economic security of the protocol is therefore tied to the same price volatility curve as data persistence.
2.2 Walrus: Dual Token Economic Model
Walrus splits functional responsibilities into two tokens:
$WAL: The economic unit of the storage layer. Users pay for rental space with WAL, and node operators earn WAL rewards through staking and storing data fragments, with the rewards also linked to the weight of their delegated staking.
$SUI: The gas token used for coordinating transactions on the chain. Any transactions such as uploads, renewals, penalties, etc., conducted on Sui require the consumption of SUI, which is rewarded to Sui validator nodes instead of Walrus storage nodes.
This separation keeps the storage economy clear: the value of WAL is only affected by data storage demand and rental duration, and is not disturbed by DEX trading or NFT booms on Sui. At the same time, Walrus can also inherit Sui's liquidity, cross-chain bridges, and fiat gateways—most Sui builders already hold SUI, so the marginal cost of introducing WAL is low.
However, the dual-token model also has the problem of incentive fragmentation. Walrus nodes cannot participate in the fee income from SUI, so the price of WAL must be sufficient to independently support hardware, bandwidth, and return expectations. If the price of WAL stagnates while SUI gas skyrockets, the user cost will rise, but the storage party will have no direct income. Conversely, the explosion of DeFi on Sui boosts the earnings of verification nodes, but is unrelated to Walrus nodes. Therefore, to maintain long-term balance, it is necessary to actively optimize the economic model: the storage price needs to flexibly fluctuate based on hardware costs, demand cycles, and WAL market depth.
2.3 Design Summary
In short, Irys offers a unified and concise user experience but assumes risks centrally; Walrus, on the other hand, delineates boundaries at the token level, bringing about more refined economic accounting, but needs to handle the issues of two market systems and fee distribution. Builders should weigh their options when choosing: whether they prefer a seamless experience or favor the separation of economic risks to align with their product planning and funding strategies.
3. Data Persistence and Redundancy Strategy
3.1 Walrus: Implementing lightweight high reliability using erasure coding
Walrus divides each data block (blob) into k data shards and adds m redundant parity shards (using the RedStuff encoding algorithm). This technique is similar to RAID or Reed-Solomon coding but is optimized for decentralized environments with high node variability. You can reconstruct the original file by selecting any k shards from the k + m shards, providing two advantages:
High space efficiency: Under typical parameters (approximately 5 times expansion), the required storage space is reduced by half compared to traditional 10 times replication schemes. In simple terms, storing 1GB of data on Walrus would require an overall network capacity of about 5GB (shards distributed across multiple nodes), while a traditional full replication system might need 10GB to achieve similar security.
Strong on-demand repair capability: The encoding method of Walrus not only saves space but also bandwidth. When a node goes offline, the network only reconstructs the missing shards instead of the entire file, significantly reducing bandwidth costs. This self-healing mechanism requires downloading approximately the size of the lost shards in data (i.e., O(blob_size/ number of shards )), while traditional replication systems usually require O(blob_size) worth of data.
Each shard and its allocation to nodes will exist in the form of objects on Sui. Walrus rotates the staking committee for each epoch, challenges node availability through cryptographic proofs, and automatically re-encodes when node loss exceeds the safety threshold. This mechanism, while complex (involving two networks, multiple shards, and frequent validations), can achieve the highest durability with minimal capacity.
3.2 Irys: A conservative but robust multi-copy mechanism
Irys has chosen a more primitive and direct durability method: every 16TB data partition is fully stored by 10 staking miners, each maintaining a complete copy. The protocol prevents double counting of the same hard drive by introducing a "salt value" for specific miners (Matrix Packing technology). The system continuously verifies the reading of node hard drives through "proof-of-useful-work" to ensure that every byte truly exists; otherwise, miners will be penalized and have their staked assets deducted.
In practice, whether the data is available depends on: Is there at least one response to the inquiry among the 10 miners? If a miner fails to verify, the system will immediately initiate a re-copy to maintain the standard of 10 copies. The cost of this strategy is up to 10 times the data storage redundancy, but the logic is straightforward, and all states are centralized on a single chain.
3.3 Design Summary
Walrus focuses on: addressing the frequent replacement of nodes through efficient coding strategies and Sui's object model, ensuring data persistence without increasing costs. Irys, on the other hand, believes that as hardware costs decline rapidly, a more direct and heavier multi-replica mechanism is actually more reliable and worry-free in practical engineering.
If you need to store PB-level archival data and can accept higher protocol complexity, Walrus's erasure coding is more advantageous in terms of cost per byte. However, if you value operational simplicity (one chain, one proof, sufficient redundancy) and believe that hardware expenses are negligible compared to product delivery speed, Irys's 10-replica mechanism can provide durability assurance with minimal consideration.
4. Programmable Data and On-Chain Computation
4.1 Irys: Native support for data smart contracts
Due to the fact that storage, consensus mechanisms, and the Irys virtual machine (IrysVM) share the same ledger, contracts can easily call the read_blob(id, offset, length) method just as they read their own state. During block execution, miners stream the requested data segments directly into the virtual machine, perform deterministic checks, and continue processing the results in the same transaction. No oracles, no user parameter passing, and no off-chain intermediaries are needed.
This programmable data structure can achieve the following use cases:
Media NFTs: Metadata, high-resolution images, and royalty logic are all on-chain and enforced at the byte level.
On-chain AI: Perform inference tasks directly on the model weights stored in the partition.
Big Data Analysis: Contracts can scan large datasets such as logs, gene files, etc., without the need for external bridging.
Although gas costs increase with the number of bytes read, the user experience remains a transaction priced in IRYS.
4.2 Walrus: "Verify before Calculate" Model
Since Walrus cannot stream large files directly into the Move virtual machine, it adopts the "hash commitment + witness" design pattern:
When users store a blob, Walrus will record its content hash on Sui;
After that, any caller can submit the corresponding data fragment along with a lightweight proof that the fragment is correct (such as a Merkle path or a full hash);
The Sui contract will recalculate the hash and compare it with the Walrus metadata. If the verification is successful, trust the data and execute the subsequent logic.
Advantages:
Available for immediate use, no modifications to the L1 protocol are required;
Sui verification nodes do not need to perceive GB-level big data content.
Limit:
Manual data retrieval required: The caller must pull data from the Walrus gateway or node and package limited-length data fragments in the transaction (restricted by the transaction size of Sui);
Sharding processing overhead: For large data processing tasks, multiple microtransactions are required, or off-chain preprocessing + on-chain verification;
Double gas cost: Users need to pay SUI gas (for transaction verification) and WAL (indirectly covering underlying storage fees).
4.3 Design Summary
If your application requires processing several MB of data per block (such as on-chain AI, immersive media dApps, verifiable scientific computing processes, etc.), the embedded data API provided by Irys is more attractive.
If your scenario focuses more on data integrity proof, small media display, or when recomputation happens off-chain and only the results need to be verified on-chain, Walrus is already capable.
So, this choice is not about "whether it can be realized," but rather at which layer you wish to place the complexity: the protocol layer (Irys) or the middleware application layer (Walrus)?
5. Duration and permanence of storage
5.1 Walrus: On-demand rental model
Walrus adopts a fixed-period leasing model. When uploading data, users pay with $WAL to purchase a fixed storage duration (billed per 14 days as one epoch, with a maximum one-time purchase of approximately 2 years). After the lease term expires, if not renewed, nodes can choose to delete the data. Applications can write automatic renewal scripts through Sui smart contracts, turning "leasing" into a de facto "permanent storage," but the responsibility for renewal always lies with the uploader.
The advantage is that users do not have to prepay for capacity that may be abandoned, and pricing can track real-time hardware costs. Additionally, by setting a data lease expiration time, the network can garbage collect data that is no longer paid for, preventing the accumulation of "permanent garbage." The downside is that missing a renewal or running out of funds can lead to data loss; long-running dApps must run their own "keep-alive" bots.
5.2 Irys: Guaranteed Permanent Storage at the Protocol Layer
Irys offers a "permanent storage" option similar to Arweave. Users only need to make a one-time payment of $IRYS to fund miners' storage services for the next several hundred years in the form of an on-chain endowment (assuming storage costs continue to decline, it could cover about 200 years). After this transaction is completed, the responsibility for storage renewal is transferred to the protocol itself, and users no longer need to manage it.
The result is a "store once, use forever" user experience, which is very suitable for: NFTs, digital files, and datasets that require immutability (such as AI models). However, its drawback is the high initial cost, and this model is highly dependent on the price health of $IRYS for the coming decades, making it unsuitable for frequently updated data or temporary files.
5.3 Design Summary
If you want to control the data lifecycle and pay for actual usage, please choose Walrus; if you need unshakeable long-term data persistence and are willing to pay a premium for it, please choose Irys.
6. Network Maturity and Usage
6.1 Walrus: Capable of production-level scale
There are only 7 epochs listed on the Walrus mainnet, but there are already 103 storage operators, 121 storage nodes, and a total of 1.01 billion WAL staked. The network currently stores 14.5 million blobs (blocks of data), triggers 31.5 million blob events, has an average object size of 2.16MB, and has a total stored data volume of 1.11 petabytes (about 26% of its 4.16 petabytes of physical capacity). The upload throughput is about 1.75KB/s, and the sharded graph covers 1000 parallel shards.
The economic aspect also shows strong momentum:
Market capitalization is approximately 600 million USD, with an FDV (Fully Diluted Valuation) reaching 2.23 billion USD;
Storage Price: Approximately 55K Frost per MB (equivalent to about 0.055 WAL);
Write-in price: approximately 20K Frost per MB
The current subsidy rate is as high as 80% to accelerate early growth.
Several high-traffic brands have adopted Walrus, including Pudgy Penguins, Unchained, and Claynosaurs, all of which are building asset pipelines or data archiving backends on it. Currently, the network has 105,000 accounts, with 67 projects in integration, supporting PB-level data transmission for NFT and gaming real-world scenarios.
6.2 Irys: still in the early stages
According to the Irys public data dashboard (as of June 2025):
Contract execution TPS ≈ 13.9, storage TPS ≈ 0
Total storage data volume ≈ 199GB (officially claimed to have 280TB space)
Data transaction count: 53.7 million (of which June accounted for 13 million)
The miner system "coming soon" (uPoW mining mechanism has not been activated yet)
The cost of programmable data invocation is $0.02 per chunk, but since the permanent storage fund has not yet been established, the actual amount of data written remains very limited. Currently, the contract execution throughput performs well, but the batch storage capacity is still essentially zero, reflecting its current focus on virtual machine functionality and developer tools rather than data storage capability.
The meaning represented by the number 6.3
Walrus has reached a PB-level scale, capable of generating revenue, and has undergone rigorous testing by consumer NFT brands. Meanwhile, Irys is still in the early guidance stage, feature-rich, but requires miners to join and meet data volume requirements.
For customers assessing production readiness, Walrus's current performance is as follows:
Higher real usage: Over 14 million blobs uploaded, PB-level data storage;
Broader operational scale: over 100 operators, 1,000 shards, and more than 100 million dollars in staked amount;
Stronger ecological appeal: Leading Web3 projects have already been integrated and in use;
A clearer pricing system: WAL/Frost charges are clear and transparent, and the on-chain subsidy mechanism is visible.
Although Irys's integrated vision may have advantages in the future (such as miners going online, the realization of a permanent storage fund, and an increase in TPS), based on the current quantifiable throughput, capacity, and customer usage, Walrus has a more practical leading advantage.
Looking to the Future
Walrus and Irys represent the two ends of the on-chain storage design spectrum:
Irys consolidates storage, execution, and economic models into a single IRYS token and a dedicated L1 blockchain designed for data, providing developers with a frictionless on-chain big data access experience, along with a protocol-level commitment to "permanent storage." Consequently, development teams need to migrate to a relatively young ecosystem and accept higher hardware resource consumption.
Walrus will build the data storage layer with erasure coding on top of Sui, reusing mature consensus mechanisms, liquidity infrastructure, and development toolchains to achieve a highly cost-effective storage cost per byte. However, its modular architecture also brings additional coordination complexity, a dual-token experience, and a continued focus on "lease renewal."
Choosing which one is not a matter of "right or wrong," but depends on the bottleneck that matters most to you:
If you need deep data and computational capabilities, or a protocol-level "perpetual storage" commitment, then Irys's integrated design will be more suitable.
If you value capital efficiency, the rapid launch capability on Sui, or highly customizable control over the data lifecycle, Walrus's modular solution is a more pragmatic choice.
In the future, the two are likely to coexist in parallel during the continuous expansion of the on-chain data economy, serving different types of developers and application scenarios.
The content is for reference only, not a solicitation or offer. No investment, tax, or legal advice provided. See Disclaimer for more risks disclosure.
Sui ecosystem Walrus vs Irys data dispute
**Written by: **Ponyo
Compiled by: Sui Network
Key Summary
🔧 Architecture: Irys is a fully functional integrated Layer 1 "Data Chain" that provides native blob access for contracts, but requires a brand new set of validation nodes. Walrus is an erasure-coded storage layer built on Sui, which is easier to integrate but requires cross-layer coordination.
💰 Economic Model: Irys adopts a single token IRYS to unify payment fees and rewards, simplifying user experience, but with higher price volatility risks. Walrus, on the other hand, divides functionality into two tokens: WAL (for storage) and SUI (for gas), effectively isolating costs, but requiring the maintenance of two incentive systems.
📦 Persistence and Computing Power: Irys maintains 10 full replicas and streams data directly into its virtual machine; Walrus, on the other hand, uses approximately 5 times redundancy with erasure coding and hash verification, resulting in lower storage costs per GB, but a more complex protocol implementation.
💾 Compatibility: Irys offers a "one-time payment, permanent storage" donation model, which is very suitable for storing immutable data, but has high upfront costs. Walrus, on the other hand, uses a "pay-as-you-go, automatic renewal" leasing mechanism, which facilitates cost control and can quickly integrate with Sui.
📈 Adoption Status: Walrus is still in the early stages but is developing rapidly, with PB-level storage, over 100 node operators, and has been adopted by several NFT and gaming brands. In contrast, Irys is still in the pre-expansion stage, with data volume not yet reaching PB level, and the node network is still growing.
Walrus and Irys are both committed to solving the same problem: providing reliable and incentivized on-chain data storage. However, their design philosophies are completely different: Irys is a Layer 1 blockchain specifically built for data storage, integrating storage, execution, and consensus into a vertically integrated architecture; whereas Walrus is a modular storage network that relies on Sui for coordination and settlement while operating an independent off-chain storage layer.
Although the Irys team initially portrayed it as a superior "built-in" solution compared to Walrus, which was defined as a limited "external" system, in reality, both have their strengths and weaknesses, with different trade-offs. This article provides an objective comparison of Walrus and Irys across six dimensions from a technical perspective, refuting one-sided conclusions and offering developers a clear selection guide to help them determine the most suitable path based on cost, complexity, and development experience.
1. Protocol Architecture
1.1 Irys: Vertically Integrated L1
Irys embodies the classic concept of "self-sufficiency." It comes with its own consensus mechanism, staking model, and execution virtual machine (IrysVM), all of which are tightly integrated with its storage subsystem.
The verification node simultaneously assumes three roles:
Since these functions coexist within the same protocol, every layer from the block header to the data retrieval rules can be optimized for large-scale data processing. Smart contracts can directly reference on-chain files, and storage proofs will follow the consensus path for ordering regular transactions. Its advantage lies in the high consistency of the architecture: developers only need to deal with a single trust boundary and a single fee asset (IRYS), and the experience of reading data in the contract code is akin to native support.
However, the cost of this is a higher startup cost. A brand new layer of network must recruit hardware operators from scratch, build indexers, launch block explorers, strengthen clients, and cultivate development tools. In the early stages, when the verification nodes have not yet grown, block time assurance and economic security lag behind established chains. Therefore, Irys's architecture opts for deeper data integration at the expense of ecological startup speed.
1.2 Walrus: Modular Stacking Layer
Walrus takes a completely different approach. Its storage nodes operate off-chain, while Sui's high-throughput L1 handles sorting, payments, and metadata through Move smart contracts. When a user uploads a blob (data block), Walrus shards it and distributes the storage across various nodes, then records an on-chain object on Sui that contains the content hash, shard allocation, and lease terms. Renewals, forfeitures, and rewards are executed as regular Sui transactions, paying gas with SUI, but using WAL tokens as the unit of settlement for storage economics.
Relying on Sui, Walrus immediately gains the following advantages:
But the cost is the need for cross-layer coordination. Each lifecycle event (upload, renewal, deletion) must be coordinated between two semi-independent networks. Storage nodes must trust the finality of Sui while still maintaining performance during Sui congestion; meanwhile, Sui validator nodes do not verify whether the actual disk stores the data, so they must rely on Walrus's cryptographic proof system to ensure accountability. Compared to an integrated design, this architecture inevitably incurs higher latency, and some transaction fees (SUI gas) will flow to roles that do not actually store data.
1.3 Design Summary
Irys adopts a vertically integrated monolithic architecture, while Walrus is a horizontally layered modular solution. Irys has greater architectural freedom and a unified trust boundary but needs to overcome the ecological building challenges brought by cold starts. Walrus, on the other hand, leverages Sui's mature consensus system to significantly lower the access threshold for developers within the existing ecosystem, but must deal with the complex coordination between two economic domains and operator systems. There is no absolute superiority of either model; they simply have different optimization directions: one pursues coherence, while the other pursues composability.
When the choice of protocol depends on the developer's familiarity, ecological attractiveness, or launch speed, Walrus's layered model may be more practical. However, when the bottleneck lies in the coupling of deep data and computation, or when customized consensus logic is required, a chain like Irys, which is specifically designed for data, has sufficient reason to bear a heavier architectural burden.
2. Token Economics and Incentive Mechanisms
2.1 Irys: A token driving the entire protocol stack
The native token IRYS of Irys encompasses the economic model of the entire platform:
Since miners are responsible for both data storage and contract execution, computing income can compensate for the lack of storage revenue. Theoretically, when DeFi activities on Irys are robust, computing revenue will supplement data storage, thereby providing services at close to cost price; if contract traffic is low, the subsidy mechanism adjusts in reverse. This cross-subsidy mechanism helps to balance miner revenue and align the incentives of various roles within the protocol. For developers, a unified asset means fewer custody processes and a simplified user experience, particularly suitable for scenarios where users are not expected to interact with multiple tokens.
However, the downside is the risk correlation of single assets: once the price of IRYS drops, the rewards for computation and storage will decrease simultaneously, putting miners under dual pressure. The economic security of the protocol is therefore tied to the same price volatility curve as data persistence.
2.2 Walrus: Dual Token Economic Model
Walrus splits functional responsibilities into two tokens:
This separation keeps the storage economy clear: the value of WAL is only affected by data storage demand and rental duration, and is not disturbed by DEX trading or NFT booms on Sui. At the same time, Walrus can also inherit Sui's liquidity, cross-chain bridges, and fiat gateways—most Sui builders already hold SUI, so the marginal cost of introducing WAL is low.
However, the dual-token model also has the problem of incentive fragmentation. Walrus nodes cannot participate in the fee income from SUI, so the price of WAL must be sufficient to independently support hardware, bandwidth, and return expectations. If the price of WAL stagnates while SUI gas skyrockets, the user cost will rise, but the storage party will have no direct income. Conversely, the explosion of DeFi on Sui boosts the earnings of verification nodes, but is unrelated to Walrus nodes. Therefore, to maintain long-term balance, it is necessary to actively optimize the economic model: the storage price needs to flexibly fluctuate based on hardware costs, demand cycles, and WAL market depth.
2.3 Design Summary
In short, Irys offers a unified and concise user experience but assumes risks centrally; Walrus, on the other hand, delineates boundaries at the token level, bringing about more refined economic accounting, but needs to handle the issues of two market systems and fee distribution. Builders should weigh their options when choosing: whether they prefer a seamless experience or favor the separation of economic risks to align with their product planning and funding strategies.
3. Data Persistence and Redundancy Strategy
3.1 Walrus: Implementing lightweight high reliability using erasure coding
Walrus divides each data block (blob) into k data shards and adds m redundant parity shards (using the RedStuff encoding algorithm). This technique is similar to RAID or Reed-Solomon coding but is optimized for decentralized environments with high node variability. You can reconstruct the original file by selecting any k shards from the k + m shards, providing two advantages:
Each shard and its allocation to nodes will exist in the form of objects on Sui. Walrus rotates the staking committee for each epoch, challenges node availability through cryptographic proofs, and automatically re-encodes when node loss exceeds the safety threshold. This mechanism, while complex (involving two networks, multiple shards, and frequent validations), can achieve the highest durability with minimal capacity.
3.2 Irys: A conservative but robust multi-copy mechanism
Irys has chosen a more primitive and direct durability method: every 16TB data partition is fully stored by 10 staking miners, each maintaining a complete copy. The protocol prevents double counting of the same hard drive by introducing a "salt value" for specific miners (Matrix Packing technology). The system continuously verifies the reading of node hard drives through "proof-of-useful-work" to ensure that every byte truly exists; otherwise, miners will be penalized and have their staked assets deducted.
In practice, whether the data is available depends on: Is there at least one response to the inquiry among the 10 miners? If a miner fails to verify, the system will immediately initiate a re-copy to maintain the standard of 10 copies. The cost of this strategy is up to 10 times the data storage redundancy, but the logic is straightforward, and all states are centralized on a single chain.
3.3 Design Summary
Walrus focuses on: addressing the frequent replacement of nodes through efficient coding strategies and Sui's object model, ensuring data persistence without increasing costs. Irys, on the other hand, believes that as hardware costs decline rapidly, a more direct and heavier multi-replica mechanism is actually more reliable and worry-free in practical engineering.
If you need to store PB-level archival data and can accept higher protocol complexity, Walrus's erasure coding is more advantageous in terms of cost per byte. However, if you value operational simplicity (one chain, one proof, sufficient redundancy) and believe that hardware expenses are negligible compared to product delivery speed, Irys's 10-replica mechanism can provide durability assurance with minimal consideration.
4. Programmable Data and On-Chain Computation
4.1 Irys: Native support for data smart contracts
Due to the fact that storage, consensus mechanisms, and the Irys virtual machine (IrysVM) share the same ledger, contracts can easily call the read_blob(id, offset, length) method just as they read their own state. During block execution, miners stream the requested data segments directly into the virtual machine, perform deterministic checks, and continue processing the results in the same transaction. No oracles, no user parameter passing, and no off-chain intermediaries are needed.
This programmable data structure can achieve the following use cases:
Although gas costs increase with the number of bytes read, the user experience remains a transaction priced in IRYS.
4.2 Walrus: "Verify before Calculate" Model
Since Walrus cannot stream large files directly into the Move virtual machine, it adopts the "hash commitment + witness" design pattern:
Advantages:
Limit:
4.3 Design Summary
If your application requires processing several MB of data per block (such as on-chain AI, immersive media dApps, verifiable scientific computing processes, etc.), the embedded data API provided by Irys is more attractive.
If your scenario focuses more on data integrity proof, small media display, or when recomputation happens off-chain and only the results need to be verified on-chain, Walrus is already capable.
So, this choice is not about "whether it can be realized," but rather at which layer you wish to place the complexity: the protocol layer (Irys) or the middleware application layer (Walrus)?
5. Duration and permanence of storage
5.1 Walrus: On-demand rental model
Walrus adopts a fixed-period leasing model. When uploading data, users pay with $WAL to purchase a fixed storage duration (billed per 14 days as one epoch, with a maximum one-time purchase of approximately 2 years). After the lease term expires, if not renewed, nodes can choose to delete the data. Applications can write automatic renewal scripts through Sui smart contracts, turning "leasing" into a de facto "permanent storage," but the responsibility for renewal always lies with the uploader.
The advantage is that users do not have to prepay for capacity that may be abandoned, and pricing can track real-time hardware costs. Additionally, by setting a data lease expiration time, the network can garbage collect data that is no longer paid for, preventing the accumulation of "permanent garbage." The downside is that missing a renewal or running out of funds can lead to data loss; long-running dApps must run their own "keep-alive" bots.
5.2 Irys: Guaranteed Permanent Storage at the Protocol Layer
Irys offers a "permanent storage" option similar to Arweave. Users only need to make a one-time payment of $IRYS to fund miners' storage services for the next several hundred years in the form of an on-chain endowment (assuming storage costs continue to decline, it could cover about 200 years). After this transaction is completed, the responsibility for storage renewal is transferred to the protocol itself, and users no longer need to manage it.
The result is a "store once, use forever" user experience, which is very suitable for: NFTs, digital files, and datasets that require immutability (such as AI models). However, its drawback is the high initial cost, and this model is highly dependent on the price health of $IRYS for the coming decades, making it unsuitable for frequently updated data or temporary files.
5.3 Design Summary
If you want to control the data lifecycle and pay for actual usage, please choose Walrus; if you need unshakeable long-term data persistence and are willing to pay a premium for it, please choose Irys.
6. Network Maturity and Usage
6.1 Walrus: Capable of production-level scale
There are only 7 epochs listed on the Walrus mainnet, but there are already 103 storage operators, 121 storage nodes, and a total of 1.01 billion WAL staked. The network currently stores 14.5 million blobs (blocks of data), triggers 31.5 million blob events, has an average object size of 2.16MB, and has a total stored data volume of 1.11 petabytes (about 26% of its 4.16 petabytes of physical capacity). The upload throughput is about 1.75KB/s, and the sharded graph covers 1000 parallel shards.
The economic aspect also shows strong momentum:
Several high-traffic brands have adopted Walrus, including Pudgy Penguins, Unchained, and Claynosaurs, all of which are building asset pipelines or data archiving backends on it. Currently, the network has 105,000 accounts, with 67 projects in integration, supporting PB-level data transmission for NFT and gaming real-world scenarios.
6.2 Irys: still in the early stages
According to the Irys public data dashboard (as of June 2025):
The cost of programmable data invocation is $0.02 per chunk, but since the permanent storage fund has not yet been established, the actual amount of data written remains very limited. Currently, the contract execution throughput performs well, but the batch storage capacity is still essentially zero, reflecting its current focus on virtual machine functionality and developer tools rather than data storage capability.
The meaning represented by the number 6.3
Walrus has reached a PB-level scale, capable of generating revenue, and has undergone rigorous testing by consumer NFT brands. Meanwhile, Irys is still in the early guidance stage, feature-rich, but requires miners to join and meet data volume requirements.
For customers assessing production readiness, Walrus's current performance is as follows:
Although Irys's integrated vision may have advantages in the future (such as miners going online, the realization of a permanent storage fund, and an increase in TPS), based on the current quantifiable throughput, capacity, and customer usage, Walrus has a more practical leading advantage.
Walrus and Irys represent the two ends of the on-chain storage design spectrum:
Choosing which one is not a matter of "right or wrong," but depends on the bottleneck that matters most to you:
In the future, the two are likely to coexist in parallel during the continuous expansion of the on-chain data economy, serving different types of developers and application scenarios.