Edge computing moves your code from a handful of data centers to dozens or hundreds of locations worldwide — executing as close to the user as possible. In 2026, edge platforms have matured beyond simple request handlers: they support full applications, database access, AI inference, and real-time collaboration. This guide compares the leading edge platforms and covers when edge computing makes sense (and when it doesn't).
Edge Platform Comparison
| Feature | Cloudflare Workers | Deno Deploy | Vercel Edge | AWS Lambda@Edge |
|---|
| Runtime | V8 isolates (not Node.js) | Deno (V8, web standards) | Edge Runtime (subset of Node.js) | Node.js (limited) |
| Global Locations | 310+ cities | 35+ regions | 100+ regions (via Cloudflare) | 410+ (CloudFront PoPs) |
| Cold Start | <5ms (isolates, near-instant) | <10ms | <50ms | <100ms (Lambda-based) |
| Execution Time Limit | 30s (Paid), 10ms CPU (Free) | 10s (free), 60s (paid) | 30s (streaming), 10s (standard) | 30s (viewer), 5s (origin) |
| Database Access | D1 (SQLite), KV, R2, Durable Objects | Deno KV, any HTTP-accessible DB | Vercel KV, Postgres, Blob | DynamoDB, any in-region resource |
| AI Inference | Workers AI (Llama, Mistral, etc.) | Any HTTP API (fetch to OpenAI, etc.) | Via AI SDK + provider APIs | SageMaker endpoints (in-region) |
| Pricing (per 1M requests) | $0.30 + $0.02/ms CPU | $2.00 (includes 50ms CPU) | $0.60 (Pro), included in Pro/Enterprise | $0.60 + $0.00005/ms |
| Free Tier | 100K req/day, D1 (5GB), KV, R2 (10GB) | 1M req/mo, 100 GiB bandwidth | 1M req/mo (Hobby) | 1M req/mo (Free Tier) |
When Edge Computing Makes Sense
| Use Case | Edge-Friendly? | Why |
|---|
| API authentication / rate limiting | Yes — perfect for edge | Minimal latency, no database dependency, stateless |
| Personalized content (logged-in user) | Yes — with edge database | Read user data from edge KV or D1, render personalized HTML |
| Full-text search | No — too heavy | Requires dedicated search infrastructure (Elasticsearch, Meilisearch) |
| AI inference (LLM text generation) | Increasingly yes | Cloudflare Workers AI runs Llama/Mistral at the edge |
| Complex database transactions | No — use regional DB | SQL JOINs, transactions, and aggregations need a real database |
| A/B testing, feature flags | Yes — perfect for edge | Cookie-based routing, split traffic, minimal latency |
| Image optimization (resize, format) | Yes — classic edge use case | Transform images on-the-fly at the edge, cache result |
Edge Database Options
| Database | Type | Platform | Best For |
|---|
| Cloudflare D1 | SQLite (distributed) | Cloudflare Workers | Relational data at the edge, simple queries |
| Cloudflare KV | Key-value (eventually consistent) | Cloudflare Workers | Configuration, feature flags, small cached data |
| Cloudflare R2 | Object storage (S3-compatible) | Cloudflare Workers | Files, images, user uploads |
| Vercel KV (Upstash) | Redis-compatible | Vercel Edge | Session data, rate limiting, caching |
| Vercel Postgres (Neon) | Serverless PostgreSQL | Vercel Edge | Full SQL, but adds ~50ms latency from edge → nearest DB region |
| Turso | SQLite (libsql, distributed) | Any edge (HTTP) | Edge SQLite with replication, good for read-heavy workloads |
Bottom line: Cloudflare Workers is the edge platform leader — 310+ locations, near-instant cold starts, and a rich ecosystem (D1, KV, R2, AI). The edge is ideal for latency-sensitive, stateless, or lightly-stateful workloads (auth, personalization, A/B testing, image optimization). It is not a replacement for regional servers — databases, complex transactions, and long-running tasks still belong on traditional infrastructure. See also: Cloudflare Workers vs Lambda vs Deno Deploy and Vercel vs Netlify vs Cloudflare.