GET vs POST: What Differs and When to Use Each

Semantic difference

GET reads: parameters go in the URL query string, and it should be safe and idempotent, so repeated calls do not change server state. POST submits: data goes in the body and may have side effects (create an order, change data).

Engineering differences

Two misuses

1. GET that mutates: crawlers or prefetch can accidentally trigger deletes or charges;
2. POST for pure queries: you lose caching and shareable links; list filters belong in GET.

One rule

Read with GET, write with POST; prefer idempotent safe repeats as GET, and use POST for state-changing submits.

Re-balancing security and cacheability

Method choice also affects two things people overlook:

• Sensitive parameters and sessions: even with POST, keep tokens out of query strings that get logged, put them in headers or the body and mask them in logs;
• Caching and idempotency: GET being cacheable by CDNs and browsers is both a benefit and a risk; a personalised GET without Cache-Control: private can be cached and served to someone else;
• Retry semantics: GET retries safely by itself; POST needs an idempotency key, or one network timeout produces two orders;
• Prefetch and crawlers: browsers and crawlers follow links on a page, so any side-effecting GET can be triggered for you.

Batch and partial updates

Bulk creation is POST on a collection, partial updates PATCH, full replacement PUT, removal DELETE. A common symptom of muddled semantics is POST doing every write, which prevents uniform handling, per-method authorisation and rate limiting become impossible. GraphQL and gRPC express this differently, but "reads are idempotent, writes need an idempotency key" still holds.

Consistency across the API surface

1. One semantic per resource: if one endpoint takes filters in the query string, others should too, mixing them defeats intuition and makes caching and logging policies hard to apply uniformly.
2. Verify idempotency: for endpoints declared idempotent, prove it with an automated test that repeats the call and checks the result, rather than a line in the docs.
3. Logs that can reconstruct: record query conditions, request bodies and response status with sensitive fields masked, or you cannot reconstruct a disputed request.
4. Rate limits by method: reads usually tolerate higher frequency while writes need stricter limits, align limits with method semantics to avoid throttling normal queries.
5. Errors that point at the cause: a misused method should return a clear status and message suggesting the correct one, so callers fix it immediately.

Picking a method is easy; keeping it consistent across the whole API, in docs, tests and operations, is the real work.