# Comprehensive Review of Storage Optimization Techniques in Blockchain Systems
## 1 Introduction  
In the 2008 paper Bitcoin: A Peer-to-Peer Electronic Cash System [1], [PERSON] first introduced the concept of Bitcoin, which underpins blockchain technology. This technology integrates decentralized distributed storage, peer-to-peer (P2P) networking, cryptography, and consensus mechanisms [2]. Blockchain technology is now widely applied across various fields. Thanks to its security, immutability, and decentralization, blockchain is now widely used in finance [3, 4, 5, 6], healthcare [7, 8, 9, 10], logistics [11, 12, 13, 14], and education [15, 16, 17, 18].  
With the deepening application of blockchain systems, the growing number of blockchain nodes has led to increased demands on storage performance for ledger and state data. As of October 2024, the size of the Bitcoin blockchain has exceeded 606 GB [19], marking an approximate 17% increase from 517 GB a year prior, with storage demands growing each year. The more complex data requirements of Blockchain 2.0 and 3.0 further raise the bar for node storage performance [20], presenting challenges to the continued growth and scalability of blockchain technology.  
The traditional blockchain storage model relies on full replication, where each node stores the complete block information, as illustrated in Figure 1. While this high redundancy ensures data security and integrity, it also leads to substantial storage costs and resource waste [21].  
In decentralized applications (DApps), the processing demands of large-scale user data, such as in decentralized social networks or content distribution platforms, place a significant burden on blockchain storage, resulting in challenges related to data redundancyand limited scalability. In the financial sector, particularly in decentralized finance (DeFi), the rapid growth of transaction volumes requires the storage of vast transactional records, exacerbating redundancy and diminishing both scalability and data validation efficiency. In healthcare, the storage of extensive patient records and imaging data, combined with blockchain's inefficiencies in handling unstructured data, hampers data access speeds and overall system performance. Similarly, in logistics, the continuous recording of diverse information across every stage of the supply chain leads to data proliferation, raising concerns over secure storage and fast retrieval. In the education sector, the storage of complex and heterogeneous data, such as student and teacher information, poses challenges for efficient storage and querying within blockchain systems. To mitigate the issue of storage redundancy, both academia and industry have proposed various optimization strategies aimed at reducing redundant data and improving system efficiency.  
This review aims to summarize and analyze existing research on blockchain technology, with a focus on storage optimization. It critically examines prominent storage optimization approaches, identifies their associated challenges and limitations, and explores prospective research directions. By fostering technological innovation, the study seeks to provide more efficient and practical storage solutions for blockchain systems, address the diverse data storage needs across industries, and facilitate the sustained development and widespread adoption of blockchain technology.