Can SUI Emerge as the Next-Generation Infrastructure Layer Driving the Web3 Industry?
In this Post, we will delve deeply into SUI, a network that has generated significant attention for its technological strengths and explore its proposed pathway toward Web3 mass adoption. SUI is characterized as a high-performance Layer 1 network featuring the Move programming language, object orientation, and parallel processing. In recent years, numerous Layer 1 networks, such as Aptos, Monad, and BellaChain, have been seen optimizing their performance. However, SUI distinguishes itself in a landscape where mere numerical specifications make differentiation challenging.
One critical insight was shared by SUI’s Chief Product Officer, Adenia Abid, in an article posted on X in September 2024. She emphasized that the value of money fundamentally relies on trust. In any network, tokens act as a medium of exchange, but the cornerstone in creating such systems is trust. If a bug arises that undermines this trust, the repercussions could be catastrophic. Abid argues that for blockchain technology to serve as a cornerstone of the global financial system, securing the underlying code is essential; however, existing Web3 programming languages fall short, which is a driving factor behind SUI’s adoption of the Move language. This programming language was partially developed by many of SUI’s founders during their involvement in Meta’s DM project and has been further refined to meet the specific needs of SUI.
The distinctive feature of Move is its object-based architecture. This approach treats each piece of data on the blockchain as a unique entity with its own ID, enabling assets, even if identical in value, to be distinctly recognized and managed—similar to non-fungible tokens (NFTs). Relationships between ownership of these distinct objects are clearer, offering numerous advantages in various contexts. In contrast to the widely used account-based model adopted by other Layer 1 networks, the object-based model enhances data management and presents evident differences in how information is processed.
Traditional account-based models treat all data as part of a single account, centralizing management. Consequently, to update statuses for transactions, the entire account must be refreshed. While this may seem straightforward, when multiple transactions occur simultaneously, it requires sequential processing to maintain data consistency, leading to inefficiencies and increased competition risks. In contrast, SUI operates under an object-oriented paradigm where each object is processed independently. This design increases data integrity, mitigates competitive state risks, and supports more efficient processing.
SUI also leverages Narwhal and Bullshark to achieve its high processing capabilities with low latency. By isolating transaction data sharing from the decision-making regarding transaction order, overall data processing efficiency significantly rises. The traditional proof-of-stake consensus model involves individual validation by separate validators followed by sharing with a mempool for transaction approval. However, this sequential approach can create bottlenecks and unnecessary data redundancy.
To tackle these issues, SUI employs Narwhal to aggregate multiple transactions into a single batch, encrypting these batches with unique IDs for compact and efficient management. These batches are organized into a Directed Acyclic Graph (DAG), facilitating a uniform recognition of transaction data among all validators, allowing for simultaneous processing of independent batches—which ultimately enhances network performance.
Introducing Bullshark, which collaborates with Narwhal, the ordering of transactions is solidified through a two-round process involving validator consensus. In the evolving landscape of Web3, the combination of Narwhal, Bullshark, and the consensus layer of Misty aims to minimize latency and maximize throughput, allowing multiple validators to submit blocks simultaneously and further enhance overall network efficiency.
To summarize, Narwhal organizes data while ensuring validator consistency, Bullshark solidifies transaction order, and Misty propels high-speed parallel processing for industry-leading performance.
Next, let’s explore SUI’s standout features further. The Pilot Fish is SUI’s smart contract execution engine, automatically scaling transaction processing capabilities. Rather than relying on a powerful single machine, it disperses tasks across multiple machines, aligning with the horizontal scaling concept. This approach allows processing capabilities to be scaled in proportion to the number of machines, circumventing the limitations and costs tied to vertical scaling, which involves upgrading single machine specs.
The Pipeline, another vital innovation, streamlines the construction of complex transactions by grouping multiple steps into a singular operation. This ensures the entire process either succeeds or fails in unison, which is remarkably useful for decentralized finance (DeFi) and gaming applications.
Moreover, we should examine two notable protocols that underlie the SUI ecosystem: DeepBook and Waras. DeepBook operates as a liquidity layer built on SUI, utilizing a decentralized order book model to match buy and sell orders based on price and time priority. Unlike the automated market maker (AMM) systems, which are prevalent in DeFi, the order book model provides more accurate price discovery, especially for large transactions, thereby minimizing price discrepancies.
DeepBook aggregates liquidity across various DeFi protocols, enhancing overall market formation and optimizing trading prices. This not only benefits individual projects by ensuring liquidity from the onset but also promotes the broader ecosystem’s growth, leveraging SUI’s high throughput and low latency.
To sustain data management as this network scales, SUI implements storage fees and transaction fees separately to establish a sustainable storage fund. Users pay in advance for data storage, which is pooled into a fund and redistributed to validators over time. Unused storage fees can be reclaimed by deleting unutilized data, incentivizing data management and reducing strain on the network.
As data demands surge, whether from images or videos, storing large datasets entirely on-chain becomes impractical. This is where Waras, SUI’s distributed storage protocol, enters the picture, employing lazy coding techniques to efficiently partition and store data. Even if a portion of the data fragments is lost, restoration is still feasible through meticulous redundancy practices.
The rising demand for storage solutions in Web3 and AI settings presents new opportunities for use cases uniquely enabled by SUI and Waras’s advanced parallel processing capabilities. Furthermore, features like transaction sponsorship and ZK-login, which enables access through existing Web2 credentials while safeguarding user privacy via zero-knowledge proof technology, simplify onboarding for new users.
SUI strives for a transformation in user experience by addressing long-standing Web3 challenges related to complexity and accessibility—an aspiration poised to facilitate mass adoption. The technologies and protocols discussed aim to foster a more simple and intuitive experience, with enhanced developer tooling and seamless user interactions serving as pivotal components in this vision. Ultimately, SUI is not just a technology stack, but a fundamental shift toward a more accessible and engaging Web3 ecosystem.
