Feed Subscriptions vs On-Demand Reads: Setup

Managed real-time streams: Once configured, the provider (e.g., Chainlink Data Streams, Pyth Network, Chainscore Feeds) pushes updates directly to your smart contract or off-chain listener. This eliminates the need for your application to poll or manage request timing, reducing your code's complexity and potential failure points.

Upfront integration work: Requires setting up listeners (e.g., Chainlink Automation for on-chain, WebSocket clients off-chain), defining update conditions, and managing subscription lifecycles. Tools like The Graph for indexed data or Alchemy's WebSockets add setup steps before the first data point is received.

Just call a function: Begin reading data immediately using standard RPC calls (eth_call) to contracts like Uniswap's Quoter, Chainlink Price Feeds, or MakerDAO's Oracles. No persistent connections or background services are needed for initial testing and prototyping.

You manage timing and cost: Your application must implement logic for when to fetch data, handle RPC rate limits, and absorb gas costs for on-chain reads. This leads to more complex application code to manage latency, staleness, and retry logic, especially under high load.

Sub-millisecond event delivery for new blocks, transactions, or logs. Protocols like Chainlink Data Streams or The Graph's Substreams push data directly to your service, eliminating polling delay. This is critical for high-frequency trading bots, NFT mint monitors, or real-time dashboards where being first is profitable.

Reduces compute and RPC load by 90%+ compared to constant polling. Your backend listens instead of querying. This simplifies architecture, lowers costs on services like Alchemy or QuickNode, and avoids rate limits. Ideal for scaling event-driven microservices without managing complex polling logic.

Higher initial complexity requiring WebSocket connections, event stream management, and fault-tolerant consumers. Services like Ponder or Goldsky abstract this, but add vendor dependency. You must handle reconnections, backpressure, and schema evolution. A poor fit for simple prototypes or infrequent queries where complexity outweighs benefit.

Risk of missed events due to network drops or consumer downtime, creating gaps in your data layer. While services offer replay features, you must implement idempotency and checkpointing. On-demand reads provide absolute consistency for audits or reconciliations. Choose Pull for mission-critical accounting or compliance logs where every state change must be captured.

Instant setup with standard JSON-RPC (eth_getLogs, eth_getBalance). No persistent connections or stream processors needed. Use Ethers.js or Viem with any standard RPC provider. Perfect for one-off queries, wallet balance checks, or infrequent data fetches where development speed trumps latency.

Pay-per-request pricing aligns cost directly with usage. No idle WebSocket costs. You maintain full control over query logic, timing, and error handling. Best for batch processing, nightly reports, or applications with predictable, low-volume access patterns where operational overhead must be minimized.

Real-time event streams: Protocols like The Graph's Substreams or Chainlink Data Streams push data with sub-second latency. This is critical for high-frequency trading bots (e.g., on Uniswap v3) and real-time dashboards that cannot afford polling delays.

Complex setup and management: Requires maintaining WebSocket connections, handling reconnects, and managing backpressure. Services like Alchemy's Subscription API or QuickNode's WebSockets abstract this but add vendor lock-in and ongoing costs versus simple HTTP calls.

Stateless and simple: Use standard JSON-RPC calls (eth_getLogs, eth_call) via providers like Infura, Alchemy, or direct nodes. Perfect for batch processing, infrequent queries (e.g., weekly reports), and prototyping where you don't need a live feed. No connection state to manage.

Higher perceived latency and throttling risks: Polling introduces delay between events and your app's awareness. Public RPC endpoints (e.g., default Infura) have strict rate limits (e.g., 100k req/day), requiring careful design to avoid hitting caps during peak loads.