What is Pyth Network (PYTH)?

What is Pyth?

As someone who has spent years navigating the complex world of decentralized finance (DeFi) and blockchain technology, I find both Pyth Network and Chainlink to be fascinating projects that cater to different needs within this space.

Pyth Network functions as a decentralized data provider, linking blockchain systems with live market statistics like stock, cryptocurrency, and commodity prices, thereby making these data points accessible on the blockchain in real-time.

Originally debuting on the Solana platform in 2021, Pyth aims to provide top-tier data to be utilized by blockchain applications, with a special focus on decentralized finance (DeFi). Precise data feeds are crucial for this sector as they serve to determine asset prices and prevent trades that are incorrectly priced.

Unlike certain oracles that acquire data through various intermediaries, Pyth obtains data directly from leading financial institutions such as exchanges and trading firms. This direct approach enhances the swiftness and dependability of its data streams.

How Pyth Network transforms real-time data feeds

Pyth Network is streamlining the process for blockchain networks to obtain real-time market data by establishing direct connections with reliable providers such as trading companies, prominent financial institutions, and stock exchanges.

Rather than depending on third parties, Pyth retrieves asset prices directly from primary suppliers, which encompass firms spanning traditional finance and cryptocurrency markets. This direct connection empowers decentralized applications (DApps) with precise, real-time pricing data, an essential aspect for tools such as lending platforms, trading mechanisms, and tokenization systems.

What sets Pyth apart is its unwavering dedication to reliability and precision. Unlike numerous other oracles, Pyth employs a distinctive data collection method, gathering numerous data points from various providers and synthesizing them into a solitary, dependable price feed. This single feed is robust against variations or manipulation, which is vital in DeFi since even the slightest delay or inaccuracy in pricing information can result in problems like liquidation errors in lending systems or market-damaging arbitrage opportunities.

Have you heard that Pyth Network shares data through its own blockchain, Pythnet, boosting transparency and security in the oracle sector of the blockchain industry?

How Pyth Network provides accurate crypto data

The precision of Pyth Network is powered by a robust verification method and aggregate model, which leverage a vast network of data providers.

Every data source, ranging from trading platforms to financial institutions, passes asset prices and their confidence levels (a measure of the price’s reliability) to Pyth. These numerous data points are subsequently combined by Pyth’s protocol to produce one price feed for each asset, which gets updated every 0.4 seconds. By employing a “pull oracle” structure, Pyth lessens blockchain traffic and decreases costs as it only updates data when a user needs it, instead of constantly transmitting it.

To uphold data accuracy, Python uses a weighted combination technique that discards any unusual values (extreme outliers) and gives greater importance to trustworthy sources. This approach substantially decreases the likelihood of tampering or data distortion. The outcome is a dependable and precise system where asset prices are validated across several autonomous sources, guaranteeing that DeFi applications can rely on them for precision and consistency.

Have you heard? The initial blockchain oracle, known as Reality Keys, was created to overcome the inherent restrictions of smart contracts. While blockchains are self-contained and highly secure, they can’t access external information such as market prices, weather conditions, or event outcomes – data crucial for numerous real-world applications.

Key use cases of Pyth Network

By utilizing Pyth Network’s real-time data streams, decentralized finance (DeFi) tools such as decentralized exchanges (DEXs), lending platforms, stablecoins, derivative products, and yield optimization services are significantly improved.

By supplying accurate, decentralized pricing, Pyth supports responsive trading, efficient liquidations, stablecoin value pegs, risk-managed derivatives and optimized yields, ensuring stability and transparency across DeFi ecosystems. Let’s take a closer look at some of its applications: 

• Decentralized exchanges (DEXs): Pyth’s real-time data feeds power decentralized exchanges, enabling accurate price updates for assets traded across multiple chains. With DEXs like Drift Protocol on Solana, Pyth’s low-latency data helps maintain efficient price discovery and risk management. Drift, for instance, leverages Pyth’s rapid updates for features like perpetual futures and other derivatives, allowing traders to respond effectively to volatile market conditions while keeping transactions transparent and secure.
• Lending platforms: For DeFi lending protocols, reliable asset pricing is crucial for accurate loan-to-value (LTV) ratios and automatic liquidations. By feeding real-time data into lending platforms, Pyth supports collateral valuations and liquidation events that protect lenders’ interests and maintain platform stability. Protocols like ReactorFusion on ZKsync use Pyth’s pricing to handle loan values efficiently, while Solend on Solana taps into Pyth to monitor collateral risks and trigger automatic liquidations, minimizing losses in fluctuating markets.
• Stablecoins: Stablecoin platforms rely heavily on Pyth to peg their value to assets like the United States dollar, euro or other currencies and commodities. By integrating with Pyth, stablecoins such as Tether’s USDt (USDT) can maintain their value through frequent, accurate price feeds, which is vital for stablecoin reserves and protecting users from depegging risks. This stable connection to fiat or crypto-collateralized assets keeps DeFi transactions smooth and trusted, especially during market swings.
• Derivatives and structured products: In the derivatives market, Pyth enables platforms to create complex financial instruments like perpetual swaps, options and structured product vaults. Kwenta and other Synthetix projects, for example, use Pyth’s feeds to offer exposure to digital assets and real-world markets, keeping positions well-hedged and reducing risks of liquidation mismatches. Pyth’s high-frequency data also supports unique options like leveraged positions, further advancing DeFi trading options with decentralized price integrity.
• Yield optimization and other DeFi applications: Yield farming and liquidity protocols use Pyth’s price feeds to optimize rewards and manage risks associated with staking or providing liquidity. Yield farmers benefit from real-time data that tracks asset performance, helping them maximize returns. Additionally, applications across blockchain ecosystems such as Mantle’s Lendle integrate Pyth to support dynamic yield-bearing assets and liquidity pools, fostering innovation and user engagement across DeFi.

Have you heard? The biggest application built on the Pyth Network is Synthetix, which operates on the Optimism blockchain. It heavily utilizes Pyth’s low-latency price data for its Synthetix Perpetuals (Perps) v2. This connection has allowed Synthetix to introduce 40 new perpetual markets, handle close to $15 billion in trading volume, and produce significant staking fees for its users.

Timeline: The history of Pyth network

Over the past few years, Pyth Network has remained dedicated to its goal of democratizing financial information. It consistently improves its system’s structure, and contributes significantly to the growth of Decentralized Finance (DeFi) by providing accurate, rapid market data updates.

2021: Launch on Solana and first price feeds

Back in April 2021, the introduction of Pyth Network became public knowledge, with its early growth supported by Jump Crypto. In August, this project made its debut on the robust Solana blockchain, delivering rapid, low-lag price data for more than thirty different cryptocurrencies.

By the year’s end, Pyth managed to gather data from approximately 40 significant financial institutions such as exchanges and market makers. This data collection is in line with their objective to provide dependable, real-time data for use in Decentralized Finance (DeFi) applications.

2022: Expansion with Pythnet and cross-chain capabilities

2022 saw a substantial growth for Pyth Network as they introduced Pythnet, their custom proof-of-authority blockchain derived from Solana. Pythnet facilitates quicker data compilation and regular update cycles compared to before.

In August of the same year, Pyth linked up with the Wormhole connection for accessing other blockchains, thus allowing it to provide price feeds not only on Ethereum but also on BNB Smart Chain and additional platforms. This move signified Pyth’s venture into multi-chain operations, with an aim to share its real-time data with a wider Decentralized Finance (DeFi) community.

2023: Governance launch and PYTH token airdrop

In the month of November 2023, Pyth unveiled its governance token named PYTH. To foster community engagement, Pyth carried out an airdrop, distributing PYTH tokens to early adopters and active DeFi participants. This distribution empowered these holders with the ability to influence decisions related to protocol modifications and advancements through voting rights.

This event marked a substantial progression towards democratizing Pyth’s management, enabling the community to contribute opinions on matters like fee arrangements, network modifications, and expansion of the ecosystem.

2024: Multichain and institutional growth

Pyth’s multi-chain development persisted, forging collaborations and price data integrations with diverse Decentralized Finance (DeFi) solutions, including Drift Protocol and ReactorFusion.

By mid-2024, Pyth has reported amassing over $5 billion in total worth and almost occupying 10% of the oracle market, highlighting its expanding status as a reliable provider of real-time data for Decentralized Finance (DeFi) on multiple blockchain platforms.

Pyth Network vs. Chainlink: What’s the difference?

The decision between Pyth and Chainlink hinges on the specific requirements of your project. If you’re focusing on DeFi, require high-speed financial data, or have needs that are finance-centric, then Pyth might be more suitable. On the other hand, if you’re looking for a solution with diverse data options and strong support from a robust ecosystem, Chainlink could be the better choice.

Regarding the subject of oracles, it’s likely you’ve heard about Chainlink, currently one of the most popular decentralized oracle solutions in use today. Supporting more than 1,600 projects as it does, you might wonder: Why is Pyth even necessary?

Mainly, Pyth Network and Chainlink have distinct differences in where they get their data. Pyth obtains its data directly from financial institutions, exchanges, and trading firms, such as Jane Street and Binance, which guarantees high-quality data that originates from these organizations. This approach differs from Chainlink’s method of collecting data through independent node operators who often source their data from aggregators like CoinMarketCap and BraveNewCoin.

This reliance on relayers means Chainlink’s data sources are more diversified but potentially less consistent than Pyth’s directly sourced data, especially for high-frequency financial data. There are a few other key differences; let’s take a closer look at each one.

Cost efficiency and data update models

In simple terms, Pyth operates using a swift data update system where users can request information refreshes only when it’s essential, thus minimizing transaction costs. This means that updates within Pyth happen incredibly quickly, typically within 0.3 to 0.4 seconds, making it perfect for decentralized finance applications that prioritize low latency.

Instead of Chainlink, usually opt for a push system that frequently refreshes prices under certain circumstances such as price changes or time periods, which can be expensive and slower. For instance, Chainlink updates data every few seconds or minutes according to predefined conditions, making it suitable for applications where speed is less important but dependability matters more significantly.

Target audience and use cases

Pyth primarily operates within the realm of Decentralized Finance (DeFi) and financial data applications. This includes decentralized trading platforms, loan services, and derivative markets. The data provided by Pyth is specifically tuned for real-time financial transactions, as it requires accurate, high-speed information in a timely manner.

While Chainlink primarily focuses on financial applications, it also extends its support to diverse use cases beyond finance, such as insurance, gaming, and supply chain management. These sectors necessitate a wide array of different data types.

Transparency and governance

Both oracles have governance mechanisms, but Pyth’s approach leans more into the Web3 ethos.

Under the control of a Decentralized Autonomous Organization (DAO), Pyth actively solicits community feedback for making decisions regarding protocol modifications and enhancements, thereby fostering transparency.

In addition to community involvement, Chainlink’s use of multi-signature contracts raises questions about decentralization because it allows a limited number of individuals to exert substantial influence over the data streams.

In contrast to Pyth, which offers complete on-chain transparency that strengthens the belief in the accuracy of its data, Chainlink’s data operates off-chain, necessitating users to independently confirm its origin.

The future of Pyth

Pyth Network’s blueprint showcases a substantial growth in cross-chain compatibility, aiming to integrate with more than 50 blockchain platforms such as Near and Arbitrum. This expansion is intended to broaden its influence within the Decentralized Finance (DeFi) sector.

Through the provision of uninterrupted, open-access data streams across various blockchains, Pyth improves compatibility for Decentralized Finance (DeFi) tools and apps.

Our future strategy involves expanding the range of assets we cover, going beyond cryptocurrencies to encompass commodities, stocks, and foreign exchange. This will make us a versatile source of information, serving both the digital and traditional finance sectors.

Improvements aimed at lowering latency by 20% and adding more data providers to each feed are being made, enhancing the dependability of data for fast-paced trading and derivative systems. This will ensure a stronger foundation for these platforms.

In conclusion, the decentralized autonomous organization (DAO) model led by Pyth empowers stakeholders to shape its strategic decisions concerning matters such as fees and data reliability.

These actions establish Pyth as a fundamental data source for secure, instant data services within the rapidly evolving Decentralized Finance (DeFi) and Web3 sectors.