Ethereum maintains its status as a leading blockchain platform because it continuously evolves to improve its performance and capabilities. As the network grows and attracts more users, it faces significant challenges in maintaining efficiency, security, and decentralization.
One of the latest developments in Ethereum’s journey to address these challenges is PeerDAS (Peer Data Availability Sampling), a key feature of the upcoming Pectra upgrade.
The introduction of layer 2 solutions, such as roll-ups, has been one approach. However, these solutions still rely on the base layer (Ethereum mainnet) for data availability and security. The recent “blobs” feature (EIP-4844) introduced a new data type for rollups, but even with blobs, every node still had to download all rollup data, limiting throughput.
PeerDAS (Peer-to-Peer Data Availability Sampling) is the next step to solve Ethereum’s data availability bottleneck. It is essentially a way to enhance data availability without compromising the network’s decentralized nature.
Let’s break it down further.
What is PeerDAS?
PeerDAS (Peer Data Availability Sampling) is defined in Ethereum’s EIP-7594 as “a networking protocol that allows beacon nodes to perform data availability sampling (DAS) to ensure that blob data has been made available while downloading only a subset of the data”.
In simpler terms, PeerDAS enhances the way nodes in the Ethereum network share and verify data. It allows nodes to confirm the availability of blob data without every node needing to download the entire dataset. Instead, nodes share and sample portions of data over a peer network.
This method is especially beneficial for layer 2 solutions, such as roll-ups, which rely heavily on data availability from the base layer. By allowing nodes to sample data from each other, PeerDAS ensures smooth network operations without the necessity for every node to possess the complete dataset.
How PeerDAS Works
PeerDAS functions by transforming each blob into an extended data matrix and distributing its components across a peer-to-peer (P2P) network. Each blob is divided into smaller chunks and spread across numerous nodes. These nodes coordinate with each other through a process known as gossip and sampling to ensure data availability. Although no single node downloads every byte of data, collectively they manage to “cover” the entire blob.
To illustrate, consider a large block of rollup data (a blob) being divided into many smaller pieces. Each node retrieves a few random chunks from its peers and uses cryptographic proofs to verify that they align with the expected data from the block. If these samples pass the verification process, the node can be highly confident that the entire blob is accessible somewhere in the network, even though it has only seen a part of it.
In essence, PeerDAS introduces an additional layer of distributed validation on top of Ethereum’s blobs. This system lays the foundation for full “danksharding,” which is Ethereum’s ultimate plan for scaling data.
What PeerDAS Solves
Previously, every Ethereum node (or validator) had to download and store all blob data to verify it. PeerDAS changes that.
By sampling small pieces from peers, each node can efficiently check that data is published without needing the whole blob. In practical terms, nodes download only a few megabytes instead of gigabytes for each large block, yet still trust the data’s availability.
Lower node resource requirements
Because nodes only store a fraction of each blob, PeerDAS drastically cuts storage and bandwidth needs. It estimated that a full node’s storage per blob could drop from gigabytes to mere megabytes. This means that running an Ethereum validator or full node becomes cheaper and lighter.
Lower hardware requirements encourage more people to run nodes, improving decentralization.
Higher throughput for rollups
PeerDAS lets the network support more blob data per block by reducing per-node load. For example, if each node only needs 1/8 of the data, the protocol could theoretically increase blob capacity 4–8× without hurting nodes. In practice, this means Ethereum can accept far more rollup data in each block.
More on-chain data means rollups can process more transactions, driving throughput up and pushing fees down. Layer-2 rollups benefit a lot from this. They can submit more transactions securely, and users may enjoy lower fees.
Enhanced decentralization and security
By distributing data responsibility across many nodes, PeerDAS strengthens Ethereum’s trust model. If even a few nodes fail or behave maliciously, the erasure coding and peer checks ensure the data is still reconstructible.
Fewer demands on any single node mean casual or hobbyist validators can stay online, broadening the validator base. In short, PeerDAS makes scaling less of a fight against decentralization.
Challenges and Trade-Offs
PeerDAS promises big gains, but it also introduces new complexities and risks:
Block proposer workload
PeerDAS transfers the heavy demands of cryptocurrency processing and bandwidth to block builders. Clients will require optimizations, such as parallel CPU usage and fast networking, to meet tight deadlines.
To use PeerDAS, a block proposer must erasure-code all blobs in a block and generate KZG proofs for each column. This process involves gossiping tens of megabytes of data, all within a narrow proposal timeframe. Sigma Prime estimates that generating KZG proofs for just 16 blobs could take over a second on modern CPUs, potentially pushing proposers close to the 4-second attestation deadline. The proposer must then quickly broadcast the new blob-column data to peers. If a proposer fails to deliver all columns in time, the block could be rejected.
This issue has sparked a philosophical debate. Peter Szilágyi, a leading Ethereum developer, has suggested that implementing the protocol could negatively impact home stakers, particularly those with simpler computing setups, making it more challenging for them to participate. He argues that this contradicts the decentralized ethos of blockchain technology.
Protocol complexity and client bugs
PeerDAS is a significant new feature with many components, and its implementation necessitates changes to Ethereum’s peer-to-peer (P2P) and consensus layers. Developers have already faced challenges during testing. For instance, early PeerDAS development networks experienced state mismatches between clients and peer-scoring issues that led to network fragmentation.
Tasks such as decoupling custody groups and stress-testing reconstruction logic are still underway. Each Ethereum client—Lighthouse, Prysm, Teku, Lodestar, Grandine, and others—must implement a consistent approach to handling these changes, which is a complex task. Until these implementations mature, there’s a risk of forks or sync failures.
Network reliance
Because no single node holds complete blobs, data availability depends on honest participation from many nodes. In theory, erasure coding provides redundancy, but in a worst-case scenario (network partitions or coordinated attacks), some data pieces might not propagate.
Ethereum plans to mitigate this with incentives, but the specifics are not fully nailed down. The EIP suggests rewarding nodes (e.g. via staking rewards from gas fees) for serving their data and slashing those that hide it. However, these incentives are only proposals, not yet in the protocol.
Until such incentives exist, PeerDAS relies on the hope that most nodes act correctly. This is a big trade-off: we trust that erasure coding plus light-client sampling provides safety, but the security model is subtly different from “everyone has everything.”
Data retrievability
PeerDAS ensures short-term availability, but like any DAS system, it does not guarantee long-term archival. Once a blob has been confirmed available and finalized, the consensus layer may discard it (blobs are already ephemeral by design).
If applications need to access old data later, they must rely on external storage (IPFS, Arweave, etc.). This is not a flaw of PeerDAS per se, but it’s a general trade-off of DAS schemes.
Roadmap for PeerDAS Implementation
PeerDAS is currently under active development and is anticipated to play a significant role in Ethereum’s scaling strategy by the end of 2025. Development efforts began as early as 2024, and as of May 2025, the EIP is in draft status and undergoing peer review.
The introduction of proto-danksharding, which included the implementation of blobs during the Mainnet Deneb-Cancun upgrade on March 13, 2024, laid the foundation for the protocol’s implementation.
The subsequent Pectra upgrades in 2025 expanded the blob capacity and paved the way for Data Availability Sampling (DAS). This included adjustments to the blob target per block, increasing it from 3/6 to 6/9, thereby enhancing layer 2 throughput. Additionally, Ethereum’s “blob schedule” was established to manage future increases in blobs, facilitating higher data throughput even before the full rollout of PeerDAS.
The full activation of PeerDAS is expected to coincide with the Fusaka upgrade, which is planned for late 2025. Developers are already experimenting with PeerDAS on non-production networks.
Notably, in March 2025, Ethereum’s co-founder, Vitalik Buterin, expressed optimism about launching a Fusaka testnet featuring PeerDAS soon after the completion of Pectra.
While upgrade timelines are not fixed and may evolve, all indicators suggest that PeerDAS will be a fundamental component of Ethereum’s growth narrative by the end of 2025.
If it works as intended, it could bring Ethereum’s rollup throughput from today’s tens of thousands of TPS to the network’s long-term goal of 100,000+ TPS, all while preserving the trustless ethos of the blockchain.
Disclaimer: This article is intended solely for informational purposes and should not be considered trading or investment advice. Nothing herein should be construed as financial, legal, or tax advice. Trading or investing in cryptocurrencies carries a considerable risk of financial loss. Always conduct due diligence.
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