Web3 For Beginners

Litecoin (LTC) and Bitcoin (BTC) are both decentralized cryptocurrencies based on proof of work (PoW), but they differ significantly in transaction speed, fees, supply, and market positioning. Bitcoin is known for its scarcity and value storage function, often referred to as “digital gold,” while Litecoin stands out for faster transaction confirmations and lower fees, earning the title of “digital silver.”

Litecoin (LTC) is a decentralized blockchain based digital currency created by Charlie Lee in 2011. It was designed to offer faster transaction confirmations and lower fees than Bitcoin. As a PoW public blockchain that uses the Scrypt algorithm, Litecoin is often called “digital silver” and is widely used for payments, asset transfers, and crypto asset allocation. With its stable network, low fees, and strong liquidity, Litecoin remains one of the important foundational assets in the crypto market today.

GRT is the native utility token of The Graph network. It is mainly used to pay on-chain data query fees, support Indexer node staking, and participate in protocol governance. As the core incentive tool of a decentralized data indexing protocol, GRT’s value mainly comes from growth in on-chain data query demand, increased node staking demand, and the expansion of The Graph ecosystem.

The Graph and Chainlink are both Web3 infrastructure protocols, but they play different roles. The Graph focuses on blockchain data indexing and querying, providing efficient data access services for DeFi, NFT, and DAO applications. Chainlink, by contrast, provides decentralized oracle services that transmit off-chain data into smart contracts. In simple terms, The Graph is responsible for “reading on-chain data,” while Chainlink is responsible for “bringing in off-chain data.” Together, they form an important part of Web3 data infrastructure, and the value logic of their tokens, GRT and LINK, depends respectively on demand for data queries and demand for oracle calls.

The Graph (GRT) is a decentralized blockchain data indexing protocol designed to help developers access and query on-chain data more efficiently. Through technologies such as Subgraphs, Indexers, and GraphQL, it provides foundational data services for Web3 applications including DeFi, NFTs, and DAOs. GRT is the native token of The Graph network and is used for paying query fees, staking rewards, and network governance.

SkyAI (SKYAI) is a protocol focused on integrating AI with Web3 data infrastructure. By extending the MCP (Model Context Protocol), enabling multi chain data aggregation, and introducing a data liquidity mechanism, it delivers efficient on-chain data services for AI agents and decentralized applications. Its core goal is to transform fragmented on-chain data into callable and transferable resources, allowing AI models to better understand and utilize blockchain data. As AI agents and on-chain automation rapidly evolve, SkyAI is emerging as a key player in the AI and Web3 data infrastructure space.

ST is the core utility token in the Sentio ecosystem, connecting the flow of value among developers, data infrastructure, and network participants. As a key part of Sentio’s real time onchain data network, ST can be used for resource consumption, network incentives, and ecosystem collaboration, helping the platform build a sustainable data service model. By introducing the ST token mechanism, Sentio ties network resource usage to ecosystem incentives, allowing developers to access real time data services more efficiently while strengthening the long term sustainability of the broader data network.

Sentio and The Graph are both used for on-chain data indexing, but they differ clearly in their core design goals. The Graph indexes on-chain data through subgraphs and mainly serves data querying and aggregation needs. Sentio, by contrast, uses a real time indexing mechanism that emphasizes low latency data processing, visual monitoring, and automated alerting, making it more suitable for real time monitoring and risk warning scenarios.

Sentio’s real-time data indexing mechanism continuously monitors on-chain events, then parses, processes, and outputs data as soon as it is generated, enabling low latency data monitoring. Its real-time data processing flow mainly includes four stages: event monitoring, data parsing, structured processing, and real-time output, supporting DeFi protocol monitoring, security alerts, and on-chain operations analysis. Compared with traditional on-chain data platforms, Sentio places greater emphasis on real-time, event-driven processing, allowing raw blockchain logs to be quickly transformed into visual metrics and automated alert information.

Sentio (ST) is a real-time on-chain data infrastructure designed for the Web3 ecosystem, providing developers and protocols with instant data indexing, visual analytics, and automated alerting capabilities. Compared to traditional on-chain data platforms, Sentio places greater emphasis on real-time responsiveness and monitoring, enabling DeFi protocols, development teams, and analytics use cases to quickly capture blockchain events and generate actionable insights. By integrating real-time indexing, dashboard visualization, and automated alert mechanisms, Sentio delivers a more efficient data infrastructure layer for Web3 applications, playing a key role in areas such as protocol monitoring, risk alerts, and operational analytics.

The workflow of cryptocurrency OTC trading typically includes trade initiation, RFQ (Request for Quote), multiple price submissions, price selection, and final settlement. By relying on market makers to provide liquidity, OTC trading reduces slippage and avoids market impact. With the introduction of algorithmic trading, the OTC process is increasingly becoming automated, allowing institutions to execute trades efficiently and consistently across fragmented liquidity environments.

Algorithmic trading, or algo trading, refers to the use of programmed models to automate trading decisions and order execution. In the crypto OTC market, it is primarily used to optimize the RFQ, or request for quote, process and enable smart routing and liquidity aggregation, helping traders achieve best execution in a fragmented market. Through automated quote distribution, real time price analysis, and path optimization, algorithmic trading not only significantly reduces slippage and market impact, but has also become core infrastructure for institutional block trading, driving the OTC market toward greater electronic and systematic development.

In the cryptocurrency market, institutions typically execute large trades by combining RFQ (Request for Quote) with algorithmic trading. RFQ is used to obtain customized quotes from multiple liquidity providers, while algorithmic trading automates request distribution, optimizes quote selection, and ensures best execution. Together, this approach reduces slippage, minimizes market impact, and improves execution efficiency, making it a core method for institutional trading in today’s OTC markets.

RFQ, or Request for Quote, is a pricing mechanism widely used in crypto OTC trading. It allows traders to request quotes from multiple liquidity providers and select the best available price to execute a trade. Compared to traditional order book matching, RFQ helps reduce slippage, minimizes market impact, and supports large transactions. With the rise of algorithmic trading, the RFQ process is becoming increasingly automated and intelligently routed, making it a foundational component of institutional-grade trading infrastructure.

Crypto over the counter trading, or OTC, is a way to execute large transactions outside of public exchanges, typically facilitated by market makers or brokers. At its core is the RFQ, or Request for Quote mechanism, which allows traders to obtain customized pricing and complete large deals while minimizing slippage and market impact. As algorithmic trading continues to evolve, the OTC market is becoming more automated and intelligent, improving both liquidity and execution efficiency. OTC trading is best suited for high net worth individuals, institutions, and those handling large orders, but it also involves liquidity, counterparty, and regulatory risks.