Ethereum Node Storage Burden Increases: Comprehensive Analysis of State Bloat, Bottleneck Risks, and Practical Optimization Measures

Why the Growth of Ethereum’s Status Cannot Be Ignored

In the Ethereum architecture, “state” is not just a collection of account balances, but also includes all the storage variables, code, and related data of smart contracts. This state data forms the foundation of the network’s operation, and after each transaction is executed, the state will be updated.

The problem is that the state almost only increases and never decreases. With DeFi, NFTs, Layer 2, and various smart contract applications continually going live, state data shows a long-term accumulation trend. Even if certain contracts or accounts have not been used for many years, their associated data still needs to be stored by nodes and be accessible at any time. This structural design has laid the groundwork for potential “state bloat” in the future.

The underlying logic of node storage costs and state expansion.

Running a complete Ethereum node means that you need to synchronize and continuously maintain the full state data. As the state size continues to grow, the requirements for hard disk capacity, IO performance, and long-term maintenance costs for the node are also increasing correspondingly.

For ordinary individual users, this rising cost is gradually undermining the feasibility of running a node. As a result, more and more users are choosing to rely on third-party RPC services instead of maintaining their own nodes. Although this trend increases convenience of use, it also exacerbates the centralization risk at the infrastructure layer.

How state bloat evolves into node bottlenecks

Researchers from the Ethereum Foundation point out that the core risk of state bloat is not merely “storing a lot”, but rather the need for it to be “always available”. A large amount of long-term inactive data still occupies high-speed storage resources, putting greater pressure on nodes during synchronization, validation, and response to requests.

When the synchronization time of nodes is significantly extended and the threshold for new nodes to join continues to rise, the participation structure of the entire network may change. If only a few professional institutions can afford the operational costs of full nodes, then the network’s censorship resistance and decentralization characteristics will be challenged, which is precisely the potential risk that researchers have emphasized.

The principles, advantages, and challenges of the three major technical proposals

1. State Expiry (状态过期机制)

The core idea of the state expiration mechanism is that not all states need to be permanently retained in the “active state set.” For data that has not been accessed for a long time, it can be marked as expired and removed from the main state.

When these states are needed again, they can be restored through additional proofs or reconstruction mechanisms. This scheme is expected to significantly compress the scale of active states, but the challenge lies in how to introduce additional complexity without affecting user experience and security.

1. State Archive (状态分层与归档)

The status archiving scheme proposes to divide data into hot status and cold status. Hot status is used for high-frequency access, while cold status is used to store historical information with lower performance requirements.

This approach can reduce the dependency of nodes on high-speed storage without sacrificing data integrity. However, it imposes higher requirements on node architecture and client implementation, necessitating a balance between performance and consistency.

1. Partial Statelessness (Partial Stateless Node)

Some stateless architectures attempt to allow nodes to no longer maintain a complete state, but instead save a subset of the state based on their own needs, while the remaining data is obtained through external proofs or network requests.

The scheme can theoretically significantly lower the threshold for running nodes and expand the scale of participants. However, it also introduces new trust and communication models, which need to be carefully designed to avoid new centralized dependencies.

The impact on decentralization, RPC services, and ecological structure

If the state bloat issue is not alleviated, the importance of RPC service providers and infrastructure providers will continue to rise. This trend of centralization could potentially affect the neutrality of the network in extreme cases.

On the contrary, if the above technical solutions are gradually implemented, the threshold for running nodes is expected to decrease, thereby encouraging more individuals and small to medium teams to participate in node operation. This not only benefits network security but will also improve the overall infrastructure resilience of Ethereum.

Prospects and Price Factors of the ETH Network from the Perspective of Technical Governance

From a market perspective, state bloat does not immediately have a direct impact on the ETH price, but it relates to the network’s long-term scalability and decentralization quality. Investors generally regard such technical discussions as “medium to long-term structural factors.”

Against the backdrop of the current ETH price fluctuating around key ranges, the continuous optimization of the infrastructure layer helps to enhance market confidence. Although these proposals are still in the research stage, they demonstrate Ethereum’s proactive approach to addressing bottleneck issues at the technical governance level, which has positive implications for the long-term value of the network.