The Pyth Network represents a decentralized intermediary financial infrastructure that acts as a vital bridge between traditional financial markets (TradFi) and decentralized blockchain applications (DeFi).
The network is defined as a "first-party oracle" that provides real-time market data on-chain in a secure and transparent manner, reshaping the concept of market data as a decentralized public good.
Pyth Network is the largest and fastest growing first-party oracle network, currently providing over 380 price feeds across multiple asset classes, including cryptocurrencies, stocks, ETFs, forex pairs, and commodities, and supports more than 40 different blockchain networks.
The fundamental difference that sets Pyth apart from traditional oracles lies in its unique approach to data aggregation.
While the majority of oracle solutions rely on third-party data aggregators or intermediaries, Pyth obtains its data directly
from the original source: major financial institutions and trading firms that own and produce the data primarily.
Data providers in Pyth include key market participants such as Jane Street, Binance, Jump Trading, CBOE, and others. This direct approach ensures transparency and accuracy as the data comes from entities actively participating in the price discovery process.
The term "first-party oracle" is not just a marketing description, but the essence of the value that the network provides. Excluding intermediaries drastically reduces potential failure points and mitigates data manipulation risks, resulting in more current and reliable prices. This approach aims to solve the "bad inputs lead to bad outputs" problem that blockchain applications may encounter. By relying on the most trustworthy data sources in the market, Pyth enhances confidence in the protocols that use its data and makes it an ideal solution for sensitive financial applications requiring the highest levels of accuracy and integrity.
2. Technical Mechanism: How does the Pyth Network work?
Pyth Network relies on an innovative technical architecture that is entirely different from traditional oracle solutions, centered around a "pull" model.
Unlike oracles that use a "push" model and continuously push price updates on-chain regardless of demand, Pyth allows users to "pull" data only when they need it. This model significantly reduces gas costs for users, as they only incur transaction fees when requesting an update.
The network architecture consists of two main components that enable this unique model:
Pythnet is a dedicated blockchain (app-chain) built on Solana code, serving as a base computational layer for processing and aggregating data. Data providers publish their initial prices on this high-performance chain. Each price feed on Pythnet is updated several times per second.
Wormhole Protocol: Acts as a cross-chain messaging protocol, transferring aggregated and signed data from Pythnet to over 40 other blockchain networks. This wide compatibility allows developers to access Pyth data across multiple chains without needing individual deployments on each chain, making it cost-effective and scalable.
Data on Pythnet is aggregated using a weighted median algorithm. This algorithm produces a single, reliable aggregated price, along with a confidence interval that indicates the degree of certainty in the price. This mechanism protects the network from price manipulation attempts by a single source or a minority of providers, as each data source is weighted based on its accuracy of performance.
Pyth's "pull" model represents an innovative solution to the efficiency and cost problem in oracles.
While the traditional "push" model is costly as it pushes updates even if they are not used, Pyth's model places the gas cost on the user only when requested.
This design allows the network to be cost-effective while enabling providers to update data on Pythnet at a very high frequency of up to 400 milliseconds.
This high frequency of data is financially impractical in a traditional push model, but is possible in Pyth due to its smart architecture, making it ideal for time-sensitive financial applications.
