Interview: Pyth’s architecture as pull oracle has mainly driven its growth, says Michael Cahill

In just two years, Pyth Network has achieved remarkable milestones: expanding to over 55 blockchains, securing $300 billion in total volume, and integrating with more than 350 applications. To understand the factors behind this growth and its impact on the blockchain ecosystem, Invezz spoke Michael Cahill – CEO, Douro Labs (Core Contributor to Pyth).

On rapid growth

Invezz: Pyth has reported some fascinating growth numbers. What made this growth possible?

I think a big driver in this explosive growth is Pyth’s architecture as a pull oracle.

Legacy oracles, and most oracle today, are push oracles, meaning they are designed to push price updates on-chain at a set frequency.

This may have worked for use cases like borrowing and lending a few years back, but DeFi users today have higher expectations for throughput, latency, and security.

They also want to close the gap between DeFi and TradFi in terms of capability.

The Pyth Network is a pull oracle, meaning it empowers downstream users to request or pull price updates on-chain on demand—when they need these new prices. This does a few things.

Firstly, this makes Pyth far more gas efficient. In the push oracle, not every pushed price update is consumed, which is wasteful.

Users of Pyth, however, only pay for the prices they pull, even while Pyth Price Feeds update every 400 milliseconds.

This gas efficiency allows Pyth users to always have access to low latency data—the most recently updated price; furthermore, the Pyth oracle can easily scale to the blockchains where developers are building and cover all the price feeds that users demand.

Pull oracles can scale along these dimensions without worrying about accumulating ongoing gas expenditures.

Because of these advantages, Pyth has become a core infrastructural driver for over 350 applications and, to date, has secured more than $300B in total volume across 56 blockchains.

Invezz: How do you believe access to real-time market data is transforming decision-making processes in traditional sectors like equities and commodities?

Real-time market data has existed for decades, but has come with significant cost.

This cost has created a 2 tier system of those capable of paying and those who had to rely on delayed feeds. Pyth prices are available for anyone to use for free without a delay, which has democratized access.

Managing accuracy of real-time data

Invezz: What strategies do you use to maintain accuracy and timeliness providing real-time data for crypto, equities, commodities?

Pyth Price Feeds specialize in first-party data, that is, financial market data created and therefore owned by active participants of both traditional and Web3 capital markets.

By participating in the price discovery of these markets, these institutional and decentralized players effectively create live asset prices.

Unlike legacy oracles which typically source financial data from third-party sources, including aggregators like CoinGecko and CoinMarketCap, Pyth is designed to only have first-party sources.

This includes over 100 market makers, exchanges, financial institutions, and trading firms.

You’ll recognize household names like Binance, Bybit, OKX, Wintermute, and QCP Capital from the crypto-native roster of the Pyth data provider community.

Institutional data contributors include the Cboe, Jane Street, LMAX, and Susquehanna International Group.

More recently, Laser Digital from Nomura also joined from the banking world to provide data. DEXs like 0x, Cetus, and Orca are also part of this network.

The diversity of the data provider community enables the Pyth oracle to securely and reliably offer streaming price data for digital assets, forex pairs, and metals, in addition to some data sets which otherwise live behind walled gardens and paywalls—namely US equities and ETF prices.

Invezz: What are the biggest challenges you face in maintaining seamless data delivery across different blockchain platforms?

The Pyth Network is able to cover more than 50 blockchain ecosystems thanks to its pull oracle design, combined with the Pythnet appchain and the Wormhole cross-chain messaging protocol.

In short, the data providers contribute their data to the Pythnet application chain for secure and rapid aggregation: users on any Pyth-supported blockchain can request or pull a Wormhole-signed price update to their native blockchain to power their DeFi transaction.

This is a highly scalable design: all of the world’s financial data can come to the Pyth Network through the addition of more and more data providers.

The oracle can then deliver signed price data to any number of downstream applications, no matter what ecosystem they reside in.

The contributors are continually looking into ways to further reduce the latency of the Pyth Price Feeds, improve resilience and security.

Invezz: How does Pyth’s contributors work with its data provider partners to ensure consistent and reliable data flow?

As discussed earlier, the data providers specialize in first-party data.

This is a must for the oracle. Furthermore, the data providers undergo strict conformance testing before they are allowed to become an official provider.

During this testing period, their reported price and confidence intervals are monitored to ensure that they are compatible with the aggregate price and confidence values.

As a decentralized protocol, the Pyth Network’s governance mechanism is expected to be responsible for determining the next data providers.

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