Introduction

In Web3, data storage lays the groundwork for creating a decentralized, efficient, secure, and user-centric digital economy. Data availability (DA) and storage platforms are two interlinked pillars of the Web3 ecosystem, working together to power decentralized storage solutions.

What is DA?

Data Availability (DA) refers to the ability of participants in blockchain and distributed systems to access, retrieve, and verify data that is complete, accurate, and up-to-date, ensuring the system’s reliability and trustworthiness. Within the Web3 and blockchain space, DA plays a key role in ensuring that data storage solutions fulfill the following essential requirements:

• Accessibility: Data must be readily available to users and applications, necessitating robust access interfaces and retrieval mechanisms in storage solutions.
• Integrity: Stored data should remain unaltered and intact, safeguarding its original state and accuracy.
• Reliability: Storage systems need to guarantee timely access to data, avoiding disruptions due to system failures or other issues.
• Durability: Long-term data preservation is a crucial aspect of DA, ensuring data remains accessible and retrievable over extended periods.
• Consistency: DA ensures that distributed systems maintain uniformity between nodes or replicas, preventing data splits or discrepancies.
• Performance: Fast access and response times are vital, especially in use cases requiring rapid data handling.
• Interoperability: In multi-chain or cross-chain scenarios, DA involves seamless data sharing and integration across different blockchain networks.

What are Data Storage Platforms?

Data storage platforms refer to services and technologies that provide decentralized storage solutions. These platforms leverage blockchain and distributed systems to store, manage, and protect data, ensuring data security, accessibility, and immutability. Data storage platforms can be classified into cold storage and hot storage based on data access frequency and importance.

Cold Storage

Cold storage primarily stores data that is rarely accessed. This type of data may need long-term preservation but is not frequently used. Characteristics of cold storage include:

• Low Cost: Cold storage is generally low-cost because data access frequency is low, and storage performance requirements are minimal.
• High Capacity: Designed for storing large amounts of data, it is suitable for long-term preservation of extensive datasets.
• Slow Access Speed: Access speeds are slower as storage media and retrieval mechanisms prioritize cost over speed.
• High Reliability: Media such as tape libraries or archival storage systems offer high reliability, suitable for long-term data preservation.

Example: Arweave Protocol

Arweave specializes in cold data storage, such as historical records, backup files, and extensive datasets that require long-term preservation but infrequent access. Arweave’s cold storage solutions are characterized by high reliability and low cost. Its unique data verification mechanism ensures data integrity and security. Furthermore, the decentralized nature of the Arweave network empowers users with complete control over their data, enhancing censorship resistance and privacy. Thus, Arweave provides a secure, economical, and efficient storage option for data requiring long-term preservation with minimal access.

Diagram of Arweave’s Mechanism (Source: arweave)

Hot Storage

Hot storage is used to store data that is frequently accessed. This data type demands high real-time performance, requiring fast read and write capabilities. Characteristics of hot storage include:

• High Performance: Hot storage systems deliver high-speed data access to meet the needs of frequent data requests.
• Low Latency: Data access latency is minimal, suitable for applications requiring rapid responses.
• High Cost: Due to high-performance demands, hot storage typically costs more than cold storage.
• Fast Access: Data can be quickly retrieved and modified, making it suitable for frequently updated and rapidly accessed datasets.

Example: IPFS Protocol

The InterPlanetary File System (IPFS) is a distributed file system protocol designed to create a decentralized content-addressed and file storage network. By dividing files into multiple blocks stored across various nodes, IPFS enhances data redundancy and censorship resistance. It supports hot storage characteristics, enabling frequently accessed data to be retrieved and transmitted quickly. This makes IPFS ideal for applications requiring high throughput and fast access, such as dynamic website content, streaming media, and real-time data sharing. Its decentralization and efficiency make IPFS a prime hot data storage solution within the Web3 ecosystem.

Diagram of the IPFS Workflow (Source: gate.io)

Distinction Between DA and Data Storage Platforms

Data storage platforms and Data Availability (DA) play distinct roles and serve different functions within the Web3 ecosystem. Below is a comparison of their key differences:

Integration and Development of DA and Data Storage Platforms

A Data Availability Layer (DAL) is a specialized blockchain that provides DA functionality. Through decentralized verification methods such as Data Availability Sampling (DAS), DAL ensures that anyone can efficiently verify data without relying on trusted third parties. The integration of DAL with data storage platforms makes data storage more efficient and secure. For instance, Celestia provides an efficient data availability layer through its modular design, while Filecoin focuses on cold data storage and encourages users to contribute storage resources through incentive mechanisms.

Impact of Modular Blockchains on Data Storage Platforms

Modular technology is a key driver of DA development, providing infrastructure for its construction. In the Ethereum ecosystem, modular technology is applied on two levels:

1. Horizontal Modularization: Achieved through sharding technology.
2. Vertical Modularization: Achieved through a layered architecture where rollups handle transaction processing, while the mainnet focuses on DA and consensus mechanisms.

Advantages of Modular Design:

• Segregates system functions into independent layers.
• Allows for interchangeability among layers.
• Supports customized development for specific applications or industries.
• Enhances flexibility and scalability for optimized and expanded systems.

Source: celestia.org

These diverse design options offer adaptable solutions tailored to different scenarios and requirements, creating new opportunities and driving further advancements in the DA space.

The Role of DA in Data Storage Decisions

DA offers critical support when selecting the most suitable storage solution by:

• Demand Analysis: Analyzing data characteristics such as access frequency, volume, sensitivity, and timeliness to determine storage needs.
• Cost-Effectiveness Evaluation: Assessing storage, retrieval, and maintenance costs to find the most cost-efficient option.
• Performance Matching: Ensuring the storage solution meets performance requirements such as speed, latency, and throughput.
• Security and Compliance: Considering safety, privacy protection, and regulatory adherence.
• Technical Support and Community Evaluation: Evaluating service providers’ reputation, community backing, and reliability for long-term solutions.

By helping users understand their data storage needs and choose the best solutions, DA improves data management efficiency, ensures data security and compliance, and optimizes cost-effectiveness.

Comparison of Different DALs

Celestia: Known for low DA costs and excellent throughput, ideal for small to medium Layer 2 (L2) blockchains and appchains. Celestia lowers DA costs significantly, enabling these chains to allocate more resources to profit-sharing, ecosystem development, and liquidity enhancement.

EigenDA: Competitive due to its strong connection to Ethereum’s security and legitimacy, making it a reasonable choice for large L2s that need cost-effectiveness.

NEAR DA: Features simplicity, ease of implementation, and efficiency improvements. With the lowest transaction fees in Web3, it is a fast and cost-effective option, 85,000 times cheaper than Ethereum blob submissions and 30 times cheaper than Celestia.

Avail: Enhances usability by enabling lightweight clients to verify data integrity without downloading the full blockchain. Since becoming independent from Polygon, Avail has explored diverse partnerships, showcasing potential across multiple application scenarios.

The image below showcases a comparison of the key components of leading DALs, as analyzed by Avail:

Source: blog.availproject.org

Practical Example: NEAR DA

NEAR DA leverages a key part of the NEAR consensus mechanism called “Nightshade.” This system splits the network into multiple parallel shards, functioning like independent blockchains. Each shard produces a small part of a block, known as a chunk or shard segment.

Source: near.org

These chunks are combined into complete blocks, and the entire process happens at the protocol level. Users and developers don’t notice this process directly. This design ensures that NEAR maintains its consensus speed, even with large amounts of data, while giving users of NEAR DA enough time to access transaction data. This setup provides a cost-effective data availability solution for rollups, especially for high-transaction-volume chains like gaming chains.

As NEAR expands the number of shards, the data each shard needs to store decreases. Each account on NEAR could eventually have its own shard. This would enable lightweight RPC nodes that only follow the shards users care about. For L2s using NEAR DA, lightweight RPC clients could track just the shard holding the data blob contract during the retention period (e.g., for fraud proofs) or a specified time window (adjustable on the RPC node). Rollups wouldn’t need to rely on data availability sampling (DAS) and could instead use shard-specific data availability with lightweight RPCs.

In summary, NEAR provides a powerful DA solution with clear benefits: cost-effective, scalable, secure, and built with future-ready technology.

Conclusion

In the Web3 ecosystem, DA and data storage platforms work hand-in-hand to deliver robust decentralized storage solutions. DA is dedicated to ensuring data accessibility and integrity, leveraging blockchain technology for secure data access and seamless smart contract interactions. On the other hand, data storage platforms provide decentralized storage services, guaranteeing the persistence and backup of data. Together, they enhance data management efficiency, strengthen security and compliance, and optimize costs. As blockchain technology evolves, the collaboration between DA and data storage platforms will play an even more crucial role, fostering innovation and driving new opportunities in decentralized storage.

Source

1. Ethereum, https://ethereum.org/en/developers/docs/data-availability/
2. X, https://x.com/AvailProject/status/1826060156427448452
3. Near, https://docs.near.org/build/chain-abstraction/data-availability
4. Near, https://pages.near.org/blog/why-near-data-availability/

Verified as accurate. The article is original. Upon acceptance, the copyright will belong to Gate.io.

Alawn Liu

2025.01.13