Chainlink vs Pyth: New Chain Support

On-chain aggregation via decentralized oracle networks (DONs): Data is aggregated from multiple independent nodes before being posted on-chain, providing inherent Sybil resistance. This matters for high-value DeFi protocols (e.g., Aave, Synthetix) where data manipulation resistance is non-negotiable, even on new chains.

First-party data from 90+ major publishers: Data is pulled directly from trading firms and exchanges (e.g., Jane Street, CBOE) and aggregated off-chain via a pull oracle model. This matters for perpetuals DEXs and high-frequency trading apps (e.g., Drift, Hyperliquid) on new chains where sub-second price updates and institutional-grade data are critical.

Any user can request a price update: The "Pull" model allows protocols to fetch the latest price on-demand, paying only for the data they use. This matters for low-volume or nascent chains where minimizing baseline gas costs is essential, and for applications with bursty or event-driven data needs.

Publisher-based pull oracle: Data is pushed on-chain by first-party publishers (e.g., Jump Trading, Jane Street) and delivered in a single block via Pythnet, enabling sub-second price updates. This architecture supports 400+ price feeds with high frequency. This matters for perpetual DEXs (like Hyperliquid), options protocols, and high-frequency trading applications where latency under 500ms is critical.

Choose Chainlink if your chain's primary use case is general-purpose DeFi with high-value TVL, where the security model of decentralized node operators and a long track record (since 2019) outweighs the need for the absolute lowest latency. Ideal for: Lending/Borrowing Markets, Stablecoins, Insurance Protocols.

Choose Pyth if your chain is a high-performance L1/L2 for derivatives, where sub-second price updates and cross-chain consistency are paramount, and you trust the curated network of professional trading firms as data publishers. Ideal for: Perpetual Futures DEXs, Options Platforms, Order Book Exchanges.

Sub-second price updates: Pyth's pull oracle model delivers data on-demand with latencies under 400ms. This matters for high-frequency DeFi (e.g., perpetuals, options) where stale data directly impacts liquidation efficiency and arbitrage opportunities.

No recurring gas costs for consumers: Protocols pay only for the data they pull (update fee), avoiding continuous on-chain aggregation costs. This matters for cost-predictable dApps on high-throughput chains where gas volatility can break economic models.

70+ independent node operators securing data feeds with a proven anti-Sybil and staking model. This matters for high-value, slow-moving assets (e.g., RWAs, stablecoin reserves) where data integrity and censorship resistance are paramount over speed.

1,500+ live price feeds and deep integrations with major DeFi protocols (Aave, Compound) and L2s (Arbitrum, Optimism). This matters for interoperability-focused chains seeking immediate composability with the largest TVL pools and established developer tooling.

Single source, multi-chain delivery: Data is published once on Pythnet (Solana) and relayed via Wormhole to 50+ connected chains. This matters for rapid multi-chain deployment where maintaining feed consistency and reducing oracle management overhead is critical.

Beyond price feeds: Offers Verifiable Random Function (VRF) for NFTs/gaming, CCIP for cross-chain messaging, and Proof of Reserve audits. This matters for chains building diverse dApp suites that need a one-stop infrastructure provider beyond just market data.