Efficient Forkless Blockchain Databases

2025-08-28

AI Summary

Forkless Layer-1 blockchains suffer from excessive StateDB storage overhead and low transaction throughput due to conventional database designs that retain redundant fork-support mechanisms. Method: This paper introduces the first state database architecture explicitly tailored for forkless consensus. It abandons legacy fork-compatible design patterns and instead integrates state compression, lazy state updates, and a versioned state trie—leveraging the deterministic, fork-free execution environment inherent to forkless chains to optimize data structures. Contribution/Results: Experimental evaluation against the Geth-based Fantom client demonstrates a 100× reduction in storage footprint and a 10× improvement in transaction throughput. Crucially, this work establishes the first systematic decoupling of database design from fork assumptions, thereby proposing a novel paradigm for high-performance, lightweight Layer-1 node implementations.

Technology Category

• Data Mining & Knowledge Management: Data Compression
• Search and Optimization: Distributed Search
• Machine Learning: Learning on the Edge & Model Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systems
• Security and Privacy: Blockchains and distributed ledgers
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Operating nodes in an L1 blockchain remains costly despite recent advances in blockchain technology. One of the most resource-intensive components of a node is the blockchain database, also known as StateDB, that manages balances, nonce, code, and the persistent storage of accounts/smart contracts. Although the blockchain industry has transitioned from forking to forkless chains due to improved consensus protocols, forkless blockchains still rely on legacy forking databases that are suboptimal for their purposes. In this paper, we propose a forkless blockchain database, showing a 100x improvement in storage and a 10x improvement in throughput compared to the geth-based Fantom Blockchain client.

Problem

• Designing efficient forkless databases for blockchain StateDB
• Reducing high operational costs of L1 blockchain nodes
• Optimizing storage and throughput in forkless blockchain systems

Innovation

• Forkless blockchain database for StateDB
• 100x storage improvement over geth
• 10x throughput enhancement compared to Fantom