Push Feeds vs Read Calls: Contract Design

Push Feeds excel at providing high-frequency, low-latency data because oracles like Chainlink Data Streams or Pyth Network proactively push signed price updates on-chain. This results in sub-second finality for critical DeFi actions like liquidations. For example, Pyth's Solana feed updates every 400ms, enabling protocols like Drift and Marginfi to operate with minimal latency risk. The trade-off is higher baseline gas costs for the oracle provider, which are often subsidized but can lead to centralization pressures.

Read Calls take a different approach by using on-demand data retrieval via protocols like Chainlink Functions or API3's dAPIs. This strategy minimizes on-chain footprint and cost for low-frequency data needs, as contracts only pay gas when they explicitly request an update. This results in a trade-off of higher latency and potential single-point-of-failure during the request cycle, but offers superior flexibility for custom data types not suited to continuous feeds.

The key trade-off: If your priority is ultra-low latency and maximum uptime for core financial data (e.g., a perpetual futures DEX), choose a Push Feed from Pyth or Chainlink. If you prioritize cost efficiency, data customization, and infrequent updates (e.g., an insurance protocol checking a weather API weekly), choose a Read Call solution like Chainlink Functions.

Push Feeds excel at delivering high-frequency, real-time data with minimal latency for subscribers. This is because the feed provider (e.g., Chainlink Data Streams, Pyth Network) pre-commits gas to push updates to a dedicated on-chain storage contract. For example, Pyth's Solana pull oracle can deliver price updates with sub-second latency at a fraction of a cent in fees, enabling high-frequency trading protocols like Drift and Jupiter to operate efficiently. This model shifts the gas burden from the end-user to the data provider, creating predictable, low-cost access for all consumers of the feed.

Read Calls (Pull Oracles) take a different approach by storing data off-chain (or in a cheaper layer) and having contracts request it on-demand via authenticated APIs like Chainlink Functions or API3's dAPIs. This strategy results in a significant trade-off: it eliminates the continuous gas cost of pushing unused data, dramatically reducing operational overhead for low-frequency data (e.g., NFT floor prices updated daily). However, it introduces per-request latency (2-5 seconds for a full request-fulfill cycle) and variable gas costs paid by the requesting contract at the moment of need.

The key trade-off is between cost predictability & latency versus operational efficiency & flexibility. If your priority is sub-second latency and stable, near-zero user fees for high-frequency actions like perpetual swaps or liquidations, choose Push Feeds. They are the backbone of DeFi's most demanding applications. If you prioritize minimizing baseline gas overhead and your use case involves low-frequency data (e.g., insurance triggers, weekly rewards calculations) or dynamic, custom data aggregation, choose Read Calls. This model is ideal for event-driven contracts where cost efficiency trumps instant availability.

Decision Framework: Consider Push Feeds if: Your dApp is latency-sensitive (DeFi trading, options), you serve a high-volume user base, and you require absolute data freshness on-chain. Choose Read Calls when: Your data updates are infrequent (< hourly), you need to query custom API endpoints, your contract logic is asynchronous, or you are building on an L2 where cross-chain messaging costs for push models can be prohibitive. The optimal choice often involves a hybrid approach, using push feeds for core liquidity data and pull oracles for ancillary or custom logic.