Webhooks vs Polling vs API: How to Choose an Integration Pattern (2026)

API, polling, or webhook: which one should you actually use?

Call the API directly when you need data on demand and control timing yourself. Poll when the source has no push or you can’t accept inbound connections. Use webhooks when you need near-real-time reaction to events. In production, combine webhooks for speed with a reconciliation poll to catch misses.

Here’s the thesis I’ll defend for the rest of this post, because it’s the part most “vs” articles get wrong: webhooks are a latency optimization, not a source of truth. The source’s API is the truth. A reconciliation poll is how you stay honest. Treat a webhook as the fast lane and a periodic poll as the audit, and you stop losing data the day a deploy goes sideways.

I learned this the practical way, building Stripe billing on FinHOA. Webhooks drive provisioning in seconds, but a nightly reconciliation cron re-pulls state from Stripe and fixes anything the webhook stream dropped. Anything that touches money or access needs that second path, because webhooks will be missed — during a deploy window, a 502, or after the provider quietly exhausts its retry budget.

The whole decision collapses into one question: who initiates, and when? Everything else — latency, cost, reliability, whether you need a public endpoint — falls out of that single axis. The rest of this post is just the consequences.

What’s the real difference between an API call, polling, and a webhook?

Three patterns, one axis. The axis is direction of initiation (pull versus push) and timing (on-demand versus scheduled versus event-driven).

API: you pull, on demand

A request/response API call is you asking right now. It’s synchronous, you control the timing, and you get the freshest possible data — but only at the instant you ask. Load a profile, check a balance for a screen, validate an address at checkout. Nothing happens unless you call. This is the right tool when freshness is request-scoped: you need the data because a user is looking at it this second.

Polling: you pull, on a schedule

Polling is the same API call wrapped in a loop on a timer. You ask “anything new since cursor X?” every N seconds or minutes. The crucial property: your interval is your latency floor. Poll every 30 seconds and you learn about a change up to 30 seconds late. Polling exists to bridge the gap when you need to know about a change that happens on the other system’s clock, and that system can’t (or won’t) notify you.

Webhooks: they push, on an event

A webhook is the provider sending you one HTTP POST per discrete event, the instant it fires, to a public URL you registered. Lowest latency, least waste — but it inverts control. You now run an always-on, secured, internet-reachable endpoint, and you own delivery failures. The provider decides when; you only decide how to handle it.

Streaming: a persistent pipe

WebSockets and SSE hold a connection open for continuous high-frequency data — live prices, chat, presence, LLM token streams. That’s a different axis (one initiation, then ongoing flow), and it’s overkill for discrete business events like “payment succeeded.” I’ll come back to it.

The deciding question stays the same throughout: who initiates, and on whose schedule does fresh data arrive?

Which is faster and which is cheaper? The latency vs efficiency trade-off

Let’s put numbers on it, because the trade-off is concrete.

Latency. Polling latency is bounded by your interval. Poll every 30 seconds and worst-case staleness is 30 seconds; average is about interval/2. Webhooks deliver near-real-time — sub-second to a few seconds after the event fires. A direct API call has zero staleness if you ask exactly when you need the data, because you’re asking at the moment of need.

Efficiency, the waste math. Take a source that fires roughly 10 events a day. Poll it every 30 seconds and you make 2,880 requests per day to catch those 10 events — about 2,870 of them return nothing. The webhook equivalent is exactly 10 POSTs. Crank the interval to every 10 seconds for fresher data and you’re at 8,640 calls per day per resource, almost all empty. Polling hands you a fixed dial: tighter interval means fresher data and more cost and more 429s. You cannot get both low latency and low cost out of polling. That tension is the entire reason webhooks exist.

The honest inversion. “Webhooks are always cheaper” is false. At thousands of events per minute, a webhook flood can overwhelm your endpoint — every event becomes an inbound POST you must verify, queue, and process. At that volume, one batched list call (grab 500 changes in a single request) amortizes the per-request overhead — TLS handshake, auth, signature verification, queue enqueue — across all 500 changes, where N individual POSTs pay that overhead N times and hammer your rate limit. The per-change processing work is identical either way; what batching saves is request overhead, not total work. So efficiency depends on event frequency versus poll frequency, not on the pattern label.

Here is the head-to-head across the dimensions that actually decide the choice, for all four patterns:

When is polling actually the right choice?

Polling is not a fallback embarrassment. It’s the correct tool in several cases, and it has real implementation depth.

When to pick it

Pick polling when the source offers no webhooks at all — extremely common with older, internal, or enterprise APIs. Pick it when the work is batch or low-urgency: a nightly sync, an hourly report, end-of-day settlement, where seconds of latency are irrelevant. And pick it when you cannot expose a public HTTPS endpoint — behind a corporate firewall, on-prem, on a laptop, in a private VPC with no ingress, or a serverless function that isn’t always warm.

That last point is the decision lever most articles forget: direction of connection. Polling and direct API calls go outbound, which nearly every firewall already allows. Webhooks need the provider to reach inbound to a reachable URL. If you can’t accept inbound connections, polling wins by default, regardless of latency needs.

The cursor gotcha

Naive “updated_at greater than last_run” polling has two real bugs: clock skew between your box and the API, and lost rows when multiple records share the same timestamp at a page boundary. Use a stable, server-provided cursor or sequence id when offered (a monotonic event id, an opaque pagination token). If you must use timestamps, overlap the window slightly — re-fetch a few seconds back — and rely on idempotency to dedupe the overlap. Never assume strictly-greater-than is safe. And persist the cursor, so a restart resumes where it left off instead of replaying the world.

One real subtlety that bites people on Stripe specifically: its list endpoints return newest-first, and starting_after paginates toward older objects. So starting_after is the right tool for a one-time backfill walking history into the past — but it is the wrong tool for a recurring catch-up poll, which needs to walk forward into events newer than what you last saw. For catch-up, page with ending_before anchored on the newest id you have already processed, or filter with created[gte] and dedupe. Get this backwards and your “reconciliation” poll quietly walks into the past forever and never sees a new event.

Backoff, rate limits, idempotency

On errors or empty results, back off exponentially. On a 429, honor Retry-After. Add random jitter so many pollers (or many tenants on an aligned schedule) don’t synchronize into a thundering herd. Guard against overlap so a slow poll doesn’t kick off a second concurrent one. And note: polling needs idempotency too. Overlapping or retried polls re-deliver the same record; if processing fires a side effect, you double-fire unless your handler dedupes. Polling’s hidden virtue is that it self-heals — a missed window is caught automatically on the next poll. That’s exactly why it reappears as the safety net in the hybrid.

What goes wrong with webhooks in production that nobody mentions?

Receiving a webhook is a ten-line endpoint. Running one in production is a distributed-systems problem. Here are the four non-negotiables, then the silent killer.

1. Signature verification, on the raw body

Your URL is public. Anyone who guesses or leaks it can POST a forged “payment succeeded.” Verify the provider’s signature (e.g. the Stripe-Signature header) against the raw request bytes with your signing secret, before you do anything else. This is the bug I see shipped most: a framework that parses JSON and re-serializes it changes whitespace and key order, so the HMAC no longer matches — and someone “fixes” it by disabling verification. Read the raw body. Check a timestamp tolerance (around five minutes) to block replays. Never hand-roll the HMAC; use the SDK.

2. Idempotency, in one transaction

Delivery is at-least-once and can reorder, so the same event id arrives twice or more. Dedupe with a UNIQUE constraint on the event id. The load-bearing detail most tutorials skip: the idempotency write and the business mutation must happen in the same database transaction. If you mark an invoice paid, then crash before recording the event id, the retry double-fulfills. Claim the id and apply the effect together, or not at all.

3. Ack fast, work async

Verify the signature, enqueue the event to a background worker (Sidekiq, Celery, BullMQ, SQS), return 200, and do the slow work later. Never run email, ERP sync, or provisioning inline. A slow handler times out — providers typically read a webhook response timeout in the low tens of seconds, and Stripe’s is in that range — and the provider treats the timeout as a failed delivery and retries, amplifying both load and duplicates. The ordering is load-bearing: verify, enqueue, 200, then process.

4. Missed deliveries, the silent killer

Webhooks are best-effort, not guaranteed. If your endpoint is down for a deploy or outage past the provider’s retry window, the event is gone — and you have no idea, because the thing that would tell you is the thing that failed. Worse: a handler that returns 200 on a failed write drops the event with no error on either side. Stripe retries with exponential backoff for up to about 72 hours in live mode, then gives up (test and sandbox modes retry far fewer times over a few hours, so don’t calibrate your expectations on what you see while testing); other providers differ, but they all have a finite window. Add a dead-letter queue for events that exhaust your own retries, and “silence = failure” alerting (zero webhooks in N hours almost always means a silently broken endpoint, not a quiet day).

What is the webhook + reconciliation hybrid pattern?

This is the answer. Production systems don’t pick one — they run webhooks as the fast path and a periodic reconciliation poll as the safety net. The webhook updates state in seconds; a scheduled job independently re-pulls current state from the source API and idempotently upserts anything the webhook stream dropped.

Three design rules make it correct:

1. One shared, idempotent state-sync function feeds both paths. Both the webhook handler and the cron call the same upsert. No per-event provisioning logic that can drift between the two.
2. Reconcile against current state, not event replay. Re-fetch the object by id and upsert what’s true now. State is self-correcting; replaying a stream of missed events is not. This is why the shared core dedupes on nothing — it just converges to current truth — while the webhook path layers its own per-event idempotency on top.
3. Treat the provider API as the source of truth, your DB as a synced read-replica. Idempotency is what makes overlap harmless — the webhook and the reconciler can both deliver the same change, and your upsert no-ops the duplicate.

The two idempotency concerns are genuinely different, and conflating them is a subtle bug. The webhook path wants per-event idempotency: don’t apply event evt_X twice. The reconcile path wants state convergence: upsert current truth regardless of which event last touched the object. So the webhook handler claims the event id (UNIQUE constraint, same transaction as the write) and then calls the pure state-upsert; the reconciler calls that same state-upsert directly, with no event-id check, so it can always correct drift even when state changed after the last event you happened to record.

This is the exact spine of the FinHOA/Stripe work: one sync_subscription_to_db upsert called from the webhook handler, from the post-checkout success redirect, and from a nightly reconciliation cron. The logic can’t diverge because there’s only one copy of it.

Set the cadence by stakes: every 5 to 15 minutes for money or state-critical data, nightly for the long tail. And no, the provider’s 72-hour retries don’t replace this — retries can’t catch a handler bug that returns 200 on a failed write, or events dropped after the window closes. Here’s the minimal shape (Flask-style responses; namespaces noted are version-dependent):

import stripe

# FAST PATH: webhook handler — verify, claim event, ack fast, work async
def handle_webhook(request):
    raw = request.data  # RAW bytes, not parsed/re-serialized JSON
    try:
        event = stripe.Webhook.construct_event(
            raw, request.headers["Stripe-Signature"], WEBHOOK_SECRET
        )  # raises on bad signature or stale timestamp
    except (ValueError, stripe.SignatureVerificationError):
        # older stripe-python: stripe.error.SignatureVerificationError
        return "", 400
    enqueue(event["id"], event["data"]["object"]["id"])  # hand off, return now
    return "", 200  # ack within the provider's timeout or it retries

# WORKER: per-event idempotency (event id) wrapping the shared state upsert
def process_event(event_id, resource_id):
    with db.transaction():
        if db.exists("processed_events", id=event_id):
            return  # duplicate delivery -> no-op
        db.insert("processed_events", id=event_id)  # UNIQUE on the Event id (evt_...)
        sync_subscription_to_db(resource_id)        # same core the cron calls

# SHARED CORE: pure idempotent upsert of CURRENT state, no event-id dedupe
def sync_subscription_to_db(resource_id):
    obj = stripe.Subscription.retrieve(resource_id)  # provider = source of truth
    upsert_local_state(obj)  # converges your DB to current truth; safe to repeat

# SAFETY NET: reconciliation poll (cron, every 15 min for money/state)
def reconcile():
    newest_seen = load_newest_event_id()  # the latest evt_ we have processed
    # Stripe lists newest-first; ending_before walks the NEW events forward.
    page = stripe.Event.list(ending_before=newest_seen, limit=100)  # OUTBOUND
    fresh = list(page.auto_paging_iter())  # exhaust all new pages
    for ev in reversed(fresh):             # apply oldest-to-newest
        process_event(ev["id"], ev["data"]["object"]["id"])  # same idempotent path
    if fresh:
        save_newest_event_id(fresh[0]["id"])  # save only after the full pass

My genuine opinion, stated plainly: a webhook integration without a reconciliation job is a data-loss incident waiting for a bad deploy. I’ve never regretted writing the cron. I’ve been paged for not having it. Most of these integrations live in a dashboard or internal tool, and that’s exactly where silent drift hurts — someone notices a customer’s access is wrong days later.

When do you need WebSockets or SSE instead of webhooks?

Webhooks and streaming get conflated constantly, and mixing them up is a credibility tell. They solve different problems.

Webhooks are discrete events between servers — payment.succeeded, order.shipped. Stateless POSTs, load-balanceable across many servers, retried on failure. There’s no persistent connection; each event is its own request.

Streaming is continuous data to a client over a held-open connection — live prices, dashboards, chat, presence, collaborative cursors, LLM token streaming. The connection stays open and data flows over it.

Within streaming, SSE is the underrated default. It’s one-way server-to-client over plain HTTP/HTTPS, auto-reconnects with Last-Event-ID, and passes cleanly through proxies and firewalls. Reach for it whenever the flow is one-directional. WebSocket is full-duplex (ws/wss), but you build your own reconnection, and it usually needs sticky sessions and trickier load-balancing. Pick WebSocket only when the client must push frequently too — multiplayer, collaborative editing.

The rule: discrete events minutes or hours apart go to a webhook; a firehose of updates per second over a long-lived connection goes to streaming. And they compose — a webhook updates your backend, then SSE fans that change out to every connected browser. Don’t pay the persistent-connection ops cost (scaling, reconnects, sticky sessions) where a stateless webhook POST would do.

How do you decide? A practical decision framework

Ask these in order. The first question that resolves your case wins.

Q1 — Does the source even offer webhooks? If not, you’re polling or calling the API on demand. Done. This alone settles a surprising number of real integrations, and asking it first is the difference between textbook theory and having shipped these.

Q2 — Do you only need data when a user asks? A lookup, a render, a checkout validation? Call the request/response API at that moment. Don’t build push infrastructure for data you read on demand — that’s over-engineering.

Q3 — Do you need near-real-time reaction to events you don’t control, and can you expose a public HTTPS endpoint? Yes to both: webhooks. No public endpoint (firewall, on-prem, serverless, local dev): polling, regardless of latency preference.

Q4 — How fresh must it be? Seconds: webhooks. Minutes to hours: polling is simpler and has fewer moving parts. A continuous high-frequency stream to a UI: SSE or WebSocket.

Q5 — How bad is a missed or late event? If it touches money, fulfillment, or access: webhooks plus a reconciliation poll — the hybrid — always.

The whole framework is four questions wearing different clothes: who needs the data, how fresh, who can initiate, and what’s the cost of a miss. Automation and agent tools lean on exactly this mix — webhooks to trigger, polling to reconcile.

Frequently asked questions

Are webhooks more reliable than polling? No. They’re lower-latency but lossier. Polling self-heals — the next poll catches anything missed. Webhooks need retries plus a reconciliation poll to reach the same guarantee.

Can I skip signature verification if the URL is secret? No. A guessable or leaked URL means anyone can forge events. Always verify the HMAC against the raw request body, and check the timestamp to block replays.

How often should I poll? Match the interval to your acceptable staleness and the provider’s rate limits. Add jitter so many clients don’t synchronize, and back off exponentially on errors and 429s.

Webhook vs WebSocket — what’s the difference? A webhook is a discrete server-to-server event delivered as a stateless POST. A WebSocket is a persistent, two-way client connection for a continuous stream. Different jobs.

Do I still need a reconciliation poll if the source retries for 72 hours? Yes. Retries don’t cover handler bugs that return 200 on a failed write, or events dropped after the retry window closes — and in test mode you get far fewer retries anyway. The poll is the only thing that catches those.

What if a webhook arrives twice? Expected — delivery is at-least-once. Dedupe on the event id with a unique constraint, in the same transaction as the business write, and the duplicate becomes a harmless no-op.

So which integration pattern should you actually pick?

Four patterns, one axis. Pull on demand (API) when a user needs data right now. Pull on a schedule (polling) when the source won’t push or you can’t accept inbound connections. Push on an event (webhooks) when you need to react in seconds. Hold a persistent pipe (streaming) for continuous high-frequency flow.

And for anything touching money or access: run the hybrid. Trust webhooks for speed, never for completeness. The reconciliation poll is non-negotiable — it’s the cheapest insurance against the silent data drift that surfaces three days later as an angry support ticket.

If you want this built right the first time, this is the kind of work I do on SaaS development — and the Stripe integration post walks the exact reconciliation pattern in production code.