Push Feeds vs Pull Reads: Oracle Models

Push Feeds, exemplified by Chainlink Data Feeds, excel at providing continuous, low-latency data for high-frequency applications because they proactively broadcast updates to on-chain contracts. For example, Chainlink secures over $20B in Total Value Secured (TVS) with its push model, delivering price data for DeFi protocols like Aave and Synthetix with sub-second latency on networks like Arbitrum and Optimism. This model minimizes on-chain computation for the consumer, ideal for perpetuals or money markets requiring real-time valuations.

Pull Reads, as implemented by Pyth Network and API3's dAPIs, take a different approach by storing signed data off-chain or in a low-cost data layer. Applications "pull" updates on-demand via a verifiable pull oracle. This results in a significant trade-off: drastically lower operational costs and chain bloat (Pyth's Solana feed updates cost a fraction of a cent) at the expense of introducing latency and gas costs for the end-user at the moment of data retrieval. It shifts the cost burden from the data provider to the transaction initiator.

The key trade-off: If your priority is predictable, subsidized operating costs and ultra-low latency for users, choose a Push Feed system like Chainlink. If you prioritize minimizing protocol-side gas expenditure and can tolerate slightly higher per-user transaction costs, a Pull Read model from Pyth or API3 may be optimal. The decision hinges on whether your application logic demands data be perpetually on-chain or can be fetched just-in-time.

Push Feeds (e.g., Chainlink Data Feeds, Pyth Network) excel at providing ultra-low-latency, high-frequency data for critical on-chain functions because they proactively broadcast updates to a network of consumer contracts. For example, Pyth Network's Solana feed updates prices every 400ms with sub-second finality, making it the de facto standard for perpetual DEXs like Drift Protocol, which require real-time price accuracy for liquidations. This model minimizes on-chain latency but incurs continuous gas costs for the oracle network to push data, regardless of usage.

Pull Reads (e.g., Chainlink Functions, API3 dAPIs, Tellor) take a different approach by storing data on-chain only when a user contract explicitly requests it. This results in a fundamental trade-off: significantly lower operational costs for the oracle provider and the protocol (you only pay for data when you use it), but higher per-request latency and gas costs for the end-user's transaction. This is ideal for less time-sensitive data like insurance policy triggers, KYC verification, or batch settlement processes where cost predictability is paramount.

The key trade-off is between latency/cost structure and decentralization/coverage. If your priority is sub-second price updates for DeFi primitives like spot trading or money markets, choose a Push Feed from Chainlink or Pyth. If you prioritize cost-effective, customizable data for non-critical functions or exotic data types, choose a Pull Oracle like API3. For maximum resilience, a hybrid approach using Chainlink Data Feeds for core assets and Chainlink Functions for supplemental data is becoming a best practice for large-scale protocols.