WebSocket vs HTTP RPC Performance

Persistent, bidirectional connection: Enables instant push notifications for events like new blocks, pending transactions, or NFT transfers. This matters for building real-time dashboards, trading bots, or live NFT minting trackers where sub-second latency is critical. Avoids the overhead of repeated HTTP polling.

Negligible per-message overhead: Once the handshake is complete, data frames have minimal headers (~2-10 bytes). This matters for applications making hundreds of queries per second (e.g., DEX arbitrage bots, liquidity monitoring) as it reduces network chatter and improves response times compared to HTTP/1.1.

Stateless request/response model: Every call is independent, simplifying client logic and scaling horizontally. This matters for serverless functions (AWS Lambda, Vercel), batch processing jobs, or simple dApp frontends where connection management overhead is undesirable. Supported by every library and infrastructure provider.

Works with standard infra tools: Can be routed through CDNs (Cloudflare), cached (Redis, Varnish), and load-balanced using standard HTTP techniques. This matters for serving high volumes of read-heavy traffic (explorers, analytics pages) and achieving cost-effective scalability with providers like Infura, Alchemy, and QuickNode.

Persistent, bidirectional connection enables instant event streaming. This is critical for:

• DEX price feeds (Uniswap, 1inch) needing sub-second updates.
• NFT mint tracking (Blur, OpenSea) for live sale events.
• Wallet activity monitors that push new block confirmations. Eliminates the latency and overhead of constant HTTP polling.

Higher infrastructure overhead per active connection. Each persistent socket consumes memory and CPU, scaling cost with concurrent users. This matters for:

• Public RPC providers (Alchemy, Infura) managing connection pools.
• High-traffic dApps where 10k+ users require significant backend resources.
• Protocols where cost-per-request is a primary concern.

Stateless, request-response model simplifies caching and horizontal scaling. This is optimal for:

• Read-heavy queries (token balances, contract states) using CDN caching.
• Batch requests (eth_getLogs for historical data) processed in single calls.
• Infrastructure using load balancers (AWS ALB, Nginx) for massive throughput. Providers like QuickNode optimize HTTP endpoints for 99.9%+ uptime.

Inherent latency for real-time data requires inefficient polling loops. This creates problems for:

• DeFi arbitrage bots where 500ms polling intervals miss opportunities.
• Live dashboards that appear sluggish versus push-based WebSocket feeds.
• High-frequency applications that waste bandwidth and rate limits on empty polls. Leads to higher effective cost-per-update compared to WebSockets.

Persistent, bidirectional connection enabling instant push notifications. This matters for dApps requiring live updates like decentralized exchanges (Uniswap), NFT marketplaces (Blur), or wallet dashboards. Eliminates polling overhead for events like new blocks, pending transactions, or price feeds.

Single connection handles thousands of event subscriptions, drastically reducing network overhead versus repeated HTTP calls. This matters for high-frequency monitoring (e.g., tracking mempool for arbitrage bots) or subgraph-like data streaming. Ideal for protocols like The Graph's indexing status or Chainlink oracle updates.

Stateless request-response model supported by every client library (Ethers.js, Viem, Web3.py) and infrastructure provider (Alchemy, Infura, QuickNode). This matters for simple queries (e.g., eth_getBalance), batch requests, or environments with restrictive firewalls. The de facto standard for one-off data fetches.

Stateless nature allows easy horizontal scaling via round-robin DNS or load balancers. This matters for handling burst traffic from frontends or backend services, ensuring high availability. Services like AWS ALB or Cloudflare can distribute millions of eth_call requests across node clusters efficiently.

Persistent connections consume server resources (memory, file descriptors) and require heartbeat mechanisms to prevent timeouts. This matters for cost-optimized architectures or mobile clients with unstable networks. Providers often charge more for WebSocket endpoints due to sustained resource allocation.

Polling for state changes introduces inherent latency and wastes bandwidth with empty responses. This matters for real-time applications where sub-second updates are critical. For example, polling eth_getLogs every second for new transfers is inefficient versus subscribing via logs over WebSocket.