🔧 Architecture: Irys is a fully functional integrated Layer 1 "data chain" that provides native blob (data block) access for contracts, but requires a completely new set of validating nodes. Walrus is an erasure-coded storage layer built on Sui, which is easier to integrate but requires cross-layer coordination.
💰 Economic Model: Irys uses a single token IRYS to unify payment fees and rewards, providing a simple user experience, but with higher price volatility risks. Walrus divides its functionality into two tokens: WAL (for storage) and SUI (for gas), which effectively isolates costs, but requires maintenance of two incentive systems.
📦 Durability and Computing Power: Irys maintains 10 full replicas and streams data directly into its virtual machine; Walrus uses a method with approximately 5 times redundancy through erasure coding and hash verification, which stores each GB at a lower cost but has a more complex protocol implementation.
💾 Compatibility: Irys offers a "one-time payment, permanent storage" donation model, which is very suitable for preserving immutable data, but the upfront costs are high. Walrus adopts a "pay-as-you-go, automatic renewal" leasing mechanism, making it easier to control costs and allowing for quick integration with Sui.
📈 Adoption Status: Walrus is still in its early stages but is growing rapidly, with PB-level storage, over 100 node operators, and adoption by multiple NFT and gaming brands. In contrast, Irys is still in the pre-scaling phase, with data volume not reaching PB level, and the node network is still in the process of growth.
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 in comparison, while defining Walrus 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 offers developers a clear selection guide to help them decide on 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 a consensus mechanism, a staking model, and an execution virtual machine (IrysVM), all of which are closely integrated with its storage subsystem.
Verification nodes simultaneously assume three roles:
Store user data in the form of a complete copy;
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 handling large volumes of data. Smart contracts can directly reference on-chain files, and storage proofs will follow the consensus path that sorts ordinary transactions. The 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.
But the cost of this is a higher startup cost. A brand new layer network must start from scratch to recruit hardware operators, build indexers, launch block explorers, strengthen clients, and cultivate development tools. In the early stages, when the validation nodes have not yet grown strong, both block time assurance and economic security lag behind established chains. Therefore, Irys's architecture has chosen deeper data integration at the expense of ecological startup speed.
1.2 Walrus: Modular Stacking Layer
Walrus has taken a completely different approach. Its storage nodes operate off-chain, while Sui's high-throughput L1 is responsible for handling sorting, payments, and metadata through Move smart contracts. When a user uploads a blob (data chunk), 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 the WAL token as the settlement unit for storage economics.
Relying on Sui, Walrus immediately gains the following advantages:
Many existing Move developers can integrate directly without 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 validation nodes do not check 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 part of the 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 integrated modular solution. Irys offers greater architectural flexibility and a unified trust boundary but needs to overcome the ecological construction challenges posed by cold starts. On the other hand, Walrus leverages Sui's mature consensus system to significantly lower the entry barriers for developers in the existing ecosystem, but must deal with the collaborative complexity between two economic domains and operator systems. Neither model is absolutely superior; they simply have different optimization directions: one pursues coherence, while the other seeks composability.
When the choice of protocol depends on the developer's familiarity, ecological appeal, or launch speed, the layered model of Walrus may be more practical. However, when the bottleneck lies in the coupling of deep data and computation, or in the need for customized consensus logic, Irys, a chain specifically designed for data, also 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
Irys's native token IRYS encompasses the entire economic model of the platform:
Storage Fee: Users prepay IRYS to store data;
Execution gas: All smart contract calls are also priced in IRYS;
Miner rewards: Block subsidies, proof of storage, and transaction fees are all paid in IRYS.
Since miners are responsible for both data storage and contract execution, the computing income can compensate for the insufficient storage revenue. Theoretically, when DeFi activities on Irys are vibrant, the computing income will subsidize data storage, thus achieving services close to cost price; if contract traffic is low, the subsidy mechanism will adjust in reverse. This cross-subsidy mechanism helps balance miner revenue and aligns the incentives of various roles in the protocol. For developers, a unified asset means fewer custody processes and a simplified user experience, especially suitable for scenarios where users do not want to interact with multiple tokens.
However, the drawback lies in the risk correlation of single assets: once the price of IRYS drops, the rewards for computation and storage will decrease concurrently, putting miners under double pressure. Thus, the economic security of the protocol is tied to data persistence along the same price volatility curve.
2.2 Walrus: Dual Token Economic Model
Walrus divides functional responsibilities into two tokens:
$WAL: The economic unit of the storage layer. Users pay for leasing space with WAL, and node operators earn WAL rewards through staking and storing data fragments, with rewards also linked to the staked weight they are delegated.
$SUI: The gas token used for coordinating on-chain transactions. Any transactions on Sui, such as uploads, renewals, penalties, etc., require the consumption of SUI and are rewarded to Sui validator nodes, rather than Walrus storage nodes.
This separation keeps the storage economy clear: the value of WAL is only affected by data storage demand and rental period, and will not be disturbed by DEX trading or NFT booms on Sui. At the same time, Walrus can also inherit the liquidity, cross-chain bridges, and fiat gateways of Sui - most Sui builders already hold SUI, so the marginal cost of introducing WAL is relatively low.
However, the dual-token model also has the issue of incentive fragmentation. Walrus nodes cannot participate in the fee income of 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's cost will increase, but the storage party will have no direct income. Conversely, the explosion of DeFi on Sui drives the earnings of verification nodes, but is unrelated to Walrus nodes. Therefore, to maintain long-term balance, active optimization of the economic model is required: storage prices need to flexibly fluctuate based on hardware costs, demand cycles, and WAL market depth.
2.3 Design Summary
In short, Irys offers a unified and streamlined user experience but takes on centralized risk; Walrus clearly delineates boundaries at the token level, providing more refined economic accounting but needing to address the issues of two market systems and fee distribution. Builders should weigh their options when choosing: whether to prefer a seamless experience or a preference for 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 codes
Walrus splits 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 optimized for decentralized environments and high node variability. You can reconstruct the original file by selecting any k out of k + m shards, providing two advantages:
High space efficiency: Under typical parameters (about 5 times expansion), the required storage space is reduced by half compared to the traditional 10 times replica copy scheme. Simply put, storing 1GB of data on Walrus requires about 5GB of overall network capacity (distributed storage in shards across multiple nodes), while traditional full replica systems may require 10GB to achieve similar security.
Strong repair capability on demand: Walrus's encoding method 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 expenses. This self-healing mechanism only requires downloading data approximately equal to the size of the lost shards (i.e., O(blob_size/ number of shards )), while traditional replication systems typically require O(blob_size) of data.
Each shard and its allocation to nodes will exist in the form of objects on Sui. Walrus will rotate the staking committee every epoch, challenging node availability through cryptographic proofs, and automatically re-encode when node loss exceeds the safety threshold. Although this mechanism is complex (involving two networks, multiple shards, and frequent validations), it can achieve maximum persistence with minimal capacity.
3.2 Irys: A conservative yet robust multi-copy mechanism
Irys has opted for a more primitive and direct durability approach: every 16TB data partition is completely stored by 10 staked miners, each holding a 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 performs read verification on the nodes' 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 actual operation, whether the data is available depends on: does at least one out of 10 miners respond to the query? If a certain miner fails to validate, the system will immediately initiate re-replication 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 simple and clear, with all states concentrated 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 rapidly decline, more direct and heavier multi-replica mechanisms are actually more reliable and worry-free in practical engineering.
If you need to store PB-level archival data and can accept a higher protocol complexity, Walrus's erasure coding has a better economic advantage 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 in Smart Contracts
Since storage, consensus mechanism, and the Irys virtual machine (IrysVM) share the same ledger, contracts can easily call the read_blob(id, offset, length) method just like reading 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 within the same transaction. No oracles, no user parameter passing, and no off-chain intermediaries are needed.
This programmable data structure can implement the following use cases:
Media NFT: On-chain all metadata, high-resolution images, and royalty logic, and implement enforcement at the byte level.
On-chain AI: Performing inference tasks directly on model weights stored in partitions.
Big Data Analysis: Contracts can scan large datasets such as logs and genomic files without the need for external bridging.
Although the gas cost increases with the number of bytes read, the user experience remains a transaction priced in IRYS.
4.2 Walrus: "Validate Before Compute" Model
Due to Walrus's inability to stream large files directly into the Move virtual machine, it has adopted 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 verifies the correctness of that fragment (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:
Can be used immediately without any modifications to the L1 protocol;
Sui validation 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 or off-chain preprocessing + on-chain verification are required;
Double gas cost: Users need to pay SUI gas (for transaction verification) and WAL (indirectly pay for 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 places more emphasis on data integrity proof, small media presentation, or recomputation occurring off-chain with only the result needing verification on-chain, Walrus is already capable of handling it.
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. Storage Duration and Permanence
5.1 Walrus: On-Demand Payment Rental Model
Walrus adopts a fixed-period leasing model. When uploading data, users pay with $WAL to purchase a fixed storage period (billed per 14 days as one epoch, with a maximum one-time purchase of about 2 years). After the lease 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.
Its advantages are that users do not have to prepay for potentially forfeited capacity, 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 disadvantages are: missing a renewal or running out of funds can lead to data disappearance; long-running dApps must run their own "keep-alive" bots.
5.2 Irys: Permanent Storage Guaranteed by 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 hundreds of years in the form of an on-chain endowment (assuming storage costs continue to decline, this could cover approximately 200 years). After the 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 archives, and datasets that require immutability (such as AI models). However, its downside is the high initial cost, and this model is highly dependent on the price health of $IRYS over the next few 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 based on 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
The Walrus mainnet has only been online for 7 epochs, but it has already been running with 103 storage operators and 121 storage nodes, accumulating a stake of 1.01 billion WAL. The network has currently stored 14.5 million blobs (data blocks), triggered 31.5 million blob events, with an average object size of 2.16MB, and a total storage data volume reaching 1.11PB (approximately 26% of its 4.16PB physical capacity). The upload throughput is about 1.75KB/s, and the shard map covers 1000 parallel shards.
The economic aspect is also showing strong momentum:
Market capitalization is approximately $600 million, with an FDV (Fully Diluted Valuation) of $2.23 billion;
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%, aimed at accelerating early growth.
Several high-traffic brands have adopted Walrus, including Pudgy Penguins, Unchained, and Claynosaurs, all of which have built asset pipelines or data archiving backends on it. The network currently has 105,000 accounts, with 67 projects in integration, supporting PB-level data transmission for real-world scenarios in NFTs and gaming.
6.2 Irys: Still in Early Stage
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 of space)
Number of data transactions: 53.7 million (of which June accounted for 13 million)
The miner system "coming soon" (uPoW mining mechanism has not been enabled yet)
The cost of programmable data calls is $0.02 per chunk, but due to the permanent storage fund not being in place, the actual amount of data written remains very limited. Currently, the contract execution throughput is performing well, but the batch storage capacity is still basically zero, reflecting its current focus on virtual machine functionality and developer tools rather than data carrying capacity.
6.3 The Significance of Digital Representation
Walrus has reached PB scale, able to generate revenue, and has undergone rigorous testing by consumer NFT brands. Meanwhile, Irys is still in the early onboarding 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, 1000 shards, over 100 million dollars in staked amount;
Stronger ecological appeal: Leading Web3 projects have been integrated and are in use;
A more transparent pricing system: WAL/Frost fees are clear and transparent, and the on-chain subsidy mechanism is visible.
Although Irys's integrated vision may provide advantages in the future (such as miners going online, the implementation of a permanent storage fund, and improved TPS), based on the current quantifiable throughput, capacity, and customer usage, Walrus has a more practical leading advantage.
7. Looking to the Future
Walrus and Irys represent opposite ends of the spectrum of on-chain storage design:
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, the development team needs to migrate to a relatively young ecosystem and accept higher hardware resource consumption.
Walrus builds a data storage layer using erasure coding on top of Sui, reusing mature consensus mechanisms, liquidity infrastructure, and development toolchains, achieving a highly cost-effective storage cost per byte. However, its modular architecture also brings additional coordination complexity, a dual-token experience, and ongoing attention to "lease renewal."
Choosing which one is not a matter of "right or wrong," but rather depends on the bottleneck that matters most to you:
If you need deep data and computational capabilities, or a protocol-level "permanent 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.
Multidimensional Comparison: The Data Dispute Between Sui Ecosystem Walrus and Irys
Author: Ponyo
Compiled by: Sui Network
Key points summary
🔧 Architecture: Irys is a fully functional integrated Layer 1 "data chain" that provides native blob (data block) access for contracts, but requires a completely new set of validating nodes. Walrus is an erasure-coded storage layer built on Sui, which is easier to integrate but requires cross-layer coordination.
💰 Economic Model: Irys uses a single token IRYS to unify payment fees and rewards, providing a simple user experience, but with higher price volatility risks. Walrus divides its functionality into two tokens: WAL (for storage) and SUI (for gas), which effectively isolates costs, but requires maintenance of two incentive systems.
📦 Durability and Computing Power: Irys maintains 10 full replicas and streams data directly into its virtual machine; Walrus uses a method with approximately 5 times redundancy through erasure coding and hash verification, which stores each GB at a lower cost but has a more complex protocol implementation.
💾 Compatibility: Irys offers a "one-time payment, permanent storage" donation model, which is very suitable for preserving immutable data, but the upfront costs are high. Walrus adopts a "pay-as-you-go, automatic renewal" leasing mechanism, making it easier to control costs and allowing for quick integration with Sui.
📈 Adoption Status: Walrus is still in its early stages but is growing rapidly, with PB-level storage, over 100 node operators, and adoption by multiple NFT and gaming brands. In contrast, Irys is still in the pre-scaling phase, with data volume not reaching PB level, and the node network is still in the process of growth.
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 in comparison, while defining Walrus 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 offers developers a clear selection guide to help them decide on 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 a consensus mechanism, a staking model, and an execution virtual machine (IrysVM), all of which are closely integrated with its storage subsystem.
Verification nodes simultaneously assume 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 handling large volumes of data. Smart contracts can directly reference on-chain files, and storage proofs will follow the consensus path that sorts ordinary transactions. The 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.
But the cost of this is a higher startup cost. A brand new layer network must start from scratch to recruit hardware operators, build indexers, launch block explorers, strengthen clients, and cultivate development tools. In the early stages, when the validation nodes have not yet grown strong, both block time assurance and economic security lag behind established chains. Therefore, Irys's architecture has chosen deeper data integration at the expense of ecological startup speed.
1.2 Walrus: Modular Stacking Layer
Walrus has taken a completely different approach. Its storage nodes operate off-chain, while Sui's high-throughput L1 is responsible for handling sorting, payments, and metadata through Move smart contracts. When a user uploads a blob (data chunk), 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 the WAL token as the settlement unit 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 validation nodes do not check 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 part of the 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 integrated modular solution. Irys offers greater architectural flexibility and a unified trust boundary but needs to overcome the ecological construction challenges posed by cold starts. On the other hand, Walrus leverages Sui's mature consensus system to significantly lower the entry barriers for developers in the existing ecosystem, but must deal with the collaborative complexity between two economic domains and operator systems. Neither model is absolutely superior; they simply have different optimization directions: one pursues coherence, while the other seeks composability.
When the choice of protocol depends on the developer's familiarity, ecological appeal, or launch speed, the layered model of Walrus may be more practical. However, when the bottleneck lies in the coupling of deep data and computation, or in the need for customized consensus logic, Irys, a chain specifically designed for data, also 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
Irys's native token IRYS encompasses the entire economic model of the platform:
Since miners are responsible for both data storage and contract execution, the computing income can compensate for the insufficient storage revenue. Theoretically, when DeFi activities on Irys are vibrant, the computing income will subsidize data storage, thus achieving services close to cost price; if contract traffic is low, the subsidy mechanism will adjust in reverse. This cross-subsidy mechanism helps balance miner revenue and aligns the incentives of various roles in the protocol. For developers, a unified asset means fewer custody processes and a simplified user experience, especially suitable for scenarios where users do not want to interact with multiple tokens.
However, the drawback lies in the risk correlation of single assets: once the price of IRYS drops, the rewards for computation and storage will decrease concurrently, putting miners under double pressure. Thus, the economic security of the protocol is tied to data persistence along the same price volatility curve.
2.2 Walrus: Dual Token Economic Model
Walrus divides 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 period, and will not be disturbed by DEX trading or NFT booms on Sui. At the same time, Walrus can also inherit the liquidity, cross-chain bridges, and fiat gateways of Sui - most Sui builders already hold SUI, so the marginal cost of introducing WAL is relatively low.
However, the dual-token model also has the issue of incentive fragmentation. Walrus nodes cannot participate in the fee income of 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's cost will increase, but the storage party will have no direct income. Conversely, the explosion of DeFi on Sui drives the earnings of verification nodes, but is unrelated to Walrus nodes. Therefore, to maintain long-term balance, active optimization of the economic model is required: storage prices need to flexibly fluctuate based on hardware costs, demand cycles, and WAL market depth.
2.3 Design Summary
In short, Irys offers a unified and streamlined user experience but takes on centralized risk; Walrus clearly delineates boundaries at the token level, providing more refined economic accounting but needing to address the issues of two market systems and fee distribution. Builders should weigh their options when choosing: whether to prefer a seamless experience or a preference for 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 codes
Walrus splits 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 optimized for decentralized environments and high node variability. You can reconstruct the original file by selecting any k out of k + m shards, providing two advantages:
Each shard and its allocation to nodes will exist in the form of objects on Sui. Walrus will rotate the staking committee every epoch, challenging node availability through cryptographic proofs, and automatically re-encode when node loss exceeds the safety threshold. Although this mechanism is complex (involving two networks, multiple shards, and frequent validations), it can achieve maximum persistence with minimal capacity.
3.2 Irys: A conservative yet robust multi-copy mechanism
Irys has opted for a more primitive and direct durability approach: every 16TB data partition is completely stored by 10 staked miners, each holding a 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 performs read verification on the nodes' 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 actual operation, whether the data is available depends on: does at least one out of 10 miners respond to the query? If a certain miner fails to validate, the system will immediately initiate re-replication 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 simple and clear, with all states concentrated 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 rapidly decline, more direct and heavier multi-replica mechanisms are actually more reliable and worry-free in practical engineering.
If you need to store PB-level archival data and can accept a higher protocol complexity, Walrus's erasure coding has a better economic advantage 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 in Smart Contracts
Since storage, consensus mechanism, and the Irys virtual machine (IrysVM) share the same ledger, contracts can easily call the read_blob(id, offset, length) method just like reading 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 within the same transaction. No oracles, no user parameter passing, and no off-chain intermediaries are needed.
This programmable data structure can implement the following use cases:
Although the gas cost increases with the number of bytes read, the user experience remains a transaction priced in IRYS.
4.2 Walrus: "Validate Before Compute" Model
Due to Walrus's inability to stream large files directly into the Move virtual machine, it has adopted 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 verifies the correctness of that fragment (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:
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 places more emphasis on data integrity proof, small media presentation, or recomputation occurring off-chain with only the result needing verification on-chain, Walrus is already capable of handling it.
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. Storage Duration and Permanence
5.1 Walrus: On-Demand Payment Rental Model
Walrus adopts a fixed-period leasing model. When uploading data, users pay with $WAL to purchase a fixed storage period (billed per 14 days as one epoch, with a maximum one-time purchase of about 2 years). After the lease 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.
Its advantages are that users do not have to prepay for potentially forfeited capacity, 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 disadvantages are: missing a renewal or running out of funds can lead to data disappearance; long-running dApps must run their own "keep-alive" bots.
5.2 Irys: Permanent Storage Guaranteed by 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 hundreds of years in the form of an on-chain endowment (assuming storage costs continue to decline, this could cover approximately 200 years). After the 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 archives, and datasets that require immutability (such as AI models). However, its downside is the high initial cost, and this model is highly dependent on the price health of $IRYS over the next few 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 based on 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
The Walrus mainnet has only been online for 7 epochs, but it has already been running with 103 storage operators and 121 storage nodes, accumulating a stake of 1.01 billion WAL. The network has currently stored 14.5 million blobs (data blocks), triggered 31.5 million blob events, with an average object size of 2.16MB, and a total storage data volume reaching 1.11PB (approximately 26% of its 4.16PB physical capacity). The upload throughput is about 1.75KB/s, and the shard map covers 1000 parallel shards.
The economic aspect is also showing strong momentum:
Several high-traffic brands have adopted Walrus, including Pudgy Penguins, Unchained, and Claynosaurs, all of which have built asset pipelines or data archiving backends on it. The network currently has 105,000 accounts, with 67 projects in integration, supporting PB-level data transmission for real-world scenarios in NFTs and gaming.
6.2 Irys: Still in Early Stage
According to the Irys public data dashboard (as of June 2025):
The cost of programmable data calls is $0.02 per chunk, but due to the permanent storage fund not being in place, the actual amount of data written remains very limited. Currently, the contract execution throughput is performing well, but the batch storage capacity is still basically zero, reflecting its current focus on virtual machine functionality and developer tools rather than data carrying capacity.
6.3 The Significance of Digital Representation
Walrus has reached PB scale, able to generate revenue, and has undergone rigorous testing by consumer NFT brands. Meanwhile, Irys is still in the early onboarding 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 provide advantages in the future (such as miners going online, the implementation of a permanent storage fund, and improved TPS), based on the current quantifiable throughput, capacity, and customer usage, Walrus has a more practical leading advantage.
7. Looking to the Future
Walrus and Irys represent opposite ends of the spectrum of on-chain storage design:
Choosing which one is not a matter of "right or wrong," but rather 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.