Polling vs Webhooks: Which Should You Use?

Almost every integration eventually needs to answer one deceptively simple question: how does system A find out that something changed in system B? A payment cleared, a work order closed, an invoice posted, a shipment moved. There are exactly two mainstream ways to answer that question, and they sit at opposite ends of the design spectrum. With polling, the interested system repeatedly asks "anything new for me yet?" and usually hears "no." With webhooks, the source system pushes a message the instant the event happens and stays silent the rest of the time. Both work. Choosing wrongly is one of the most common and most expensive mistakes I see in enterprise integration, so it is worth understanding them properly. If you want the wider map of how systems talk to each other before we go deep on this one choice, start with the enterprise system integration pillar.

The short version: polling is the client asking again and again on a timer, spending most requests learning that nothing happened. A webhook is the server telling you once, exactly when the event occurs. Polling is simple, robust and wasteful. Webhooks are efficient, near-instant and operationally heavier. The right answer depends on how fresh the data must be, how often things actually change, and who controls the two systems. For the broader picture of where this choice sits, keep the integration pillar open alongside this guide.

1. The core difference

The distinction between polling and webhooks comes down to a single word: direction. In polling, the flow of initiative runs from the consumer to the producer. The consumer decides when to check, and it does the checking on its own schedule, whether or not there is anything to find. In webhooks, the flow of initiative runs the other way. The producer decides when to speak, and it speaks only when there is genuinely something to say. Everything else that differs between the two patterns, the efficiency, the latency, the operational burden, follows from that one reversal of who starts the conversation.

A homely analogy makes it stick. Polling is checking your mailbox every ten minutes to see whether the post has arrived. You walk out, you look, and most of the time the box is empty, so you walk back in having gained nothing but the knowledge that there is still nothing. A webhook is the postal service ringing your doorbell the moment a letter actually arrives. You do no work at all until there is a reason to, and when there is a reason, you learn about it immediately rather than on your next scheduled trip to the box.

Both approaches ultimately move the same information from B to A. The difference is entirely about who bears the cost of finding out, and when. That framing, who initiates and who waits, is the lens I use to reason about every integration timing decision, and it is worth holding onto through the rest of this guide.

2. How polling works

Polling is the older, simpler and more universal of the two patterns, and it is worth understanding first because webhooks are best appreciated as a solution to polling's weaknesses. In a polling integration, the consumer runs on a schedule, a timer, a cron job, a loop with a sleep, and on each tick it makes a request to the producer asking for anything new since the last time it checked. Typically it sends a marker, a timestamp or an incrementing identifier, so the producer can answer "here is what changed since then" rather than resending everything.

The producer answers one of two ways. Either there is new data, and it returns it, or there is nothing new, and it returns an empty result. The consumer processes whatever it got, updates its marker, and goes back to sleep until the next tick. That is the entire mechanism. The interval, how often the consumer checks, is the single most important design parameter, because it directly sets both how fresh the data can be and how much work the whole arrangement wastes. A short interval means fresher data and more wasted checks. A long interval means fewer wasted checks and staler data. You cannot escape that tension by tuning; you can only choose where on it to sit.

The timeline below shows the shape of a polling exchange next to a webhook exchange, and it is the clearest way to see why polling feels wasteful. Watch how many of the polling requests come back with nothing.

The picture tells the whole story. Polling scatters requests across the timeline regardless of whether anything is happening, so the event is discovered late, at the next scheduled check after it occurred, and most of the requests around it are pure overhead. The webhook fires exactly once, at the moment of the event, and the line is otherwise silent. That contrast is the reason webhooks exist.

3. How webhooks work

A webhook inverts the arrangement. Instead of the consumer asking the producer, the consumer registers a URL with the producer in advance and effectively says: when this kind of event happens, send an HTTP request to this address. From then on the consumer does nothing until the producer calls. When the event occurs, the producer makes an outbound HTTP POST to the registered URL, carrying a payload that describes what happened, the order that was created, the invoice that posted, the record that changed. The consumer receives it like any other incoming web request, processes it, and responds with a success status so the producer knows delivery worked.

The elegance is that no time or bandwidth is spent when nothing is happening. A system that changes ten times a day sends ten webhook calls a day, full stop. There is no background hum of "anything new?" traffic, and there is no delay between the event and the notification beyond the network round trip, which is usually measured in milliseconds. For anything where freshness matters, a payment confirmation, a fraud signal, a status change a user is watching on screen, that near-instant delivery is transformative compared with waiting for the next poll.

The cost of that elegance is that the consumer now has to run a publicly reachable endpoint that is available whenever the producer might call, and it has to handle the messy realities of push delivery: verifying that the call genuinely came from the producer, coping with duplicate deliveries, and absorbing bursts without falling over. A webhook is not just a nicer polling loop; it is a small piece of always-on infrastructure with its own failure modes. Because webhooks and traditional request-response APIs are so often confused, it is worth reading the dedicated API vs webhook comparison alongside this section, and if the request-response half of that pairing is unfamiliar, the REST API explainer lays the groundwork.

4. The efficiency problem with polling

The single strongest argument against polling is arithmetic, and it is worth doing the arithmetic out loud because it is easy to underestimate. Suppose you poll an API once a minute so that data is never more than about a minute stale. That is 60 requests an hour, 1,440 a day, roughly 43,000 a month, for one integration. Now suppose the underlying data actually changes ten times a day. Ten of those 1,440 daily requests returned something useful. The other 1,430, more than 99 percent, were the producer answering "nothing new" to a question it had already answered 1,429 times that day. You are paying for all 1,440: your compute, the producer's compute, the network, and often the producer's rate-limit budget and per-call pricing.

That waste scales in every dimension you care about. Multiply it by the number of records or accounts you poll, and the request count explodes. Multiply it by the number of integrations, and a polling-heavy architecture spends a substantial share of its total request volume confirming that nothing happened. Many public APIs enforce rate limits precisely because polling clients are so wasteful, which means aggressive polling does not just cost money, it can get you throttled or blocked, degrading the very freshness you were polling to achieve.

The trap to avoid: reaching for a shorter poll interval to fix latency. Halving the interval doubles the request volume and roughly doubles the waste, while only marginally improving average freshness. There is a floor below which polling simply cannot go without becoming abusive, and if you find yourself wanting sub-minute freshness from a poll, that is usually the signal that you have outgrown polling and should be receiving a push instead.

The subtler cost is latency that you cannot design away. With a one-minute poll, an event that happens one second after a check waits nearly a full minute to be noticed. On average your data is half an interval stale, and in the worst case a full interval. For back-office reconciliation that runs overnight, none of this matters. For anything a person or another automated process is waiting on in real time, that built-in lag is exactly the problem webhooks were invented to remove.

5. Head to head

Laying the two patterns side by side across the dimensions that actually drive the decision makes the trade clear. Neither column is the winner in the abstract; each wins on different rows, and your situation decides which rows matter most.

The row that decides more integrations than any other is the last-but-one: who controls timing. If you need the freshest possible reaction and the producer offers a push, the producer controlling timing is exactly what you want. If you need to throttle intake to protect a fragile downstream system, or if the producer offers no push at all, the consumer controlling timing is the feature, not the bug.

6. When polling is the right choice

For all its inefficiency, polling is frequently the correct engineering decision, and treating it as always inferior is a mistake I see confident engineers make. There are several situations where polling is not a compromise but the right tool.

• The producer offers no webhooks. This is the most common reason of all. A great many enterprise systems, legacy applications and older APIs simply do not push. If the only interface is a request-response API, polling is your only option, and arguing about elegance is moot. Read the REST API explainer for what that interface looks like.
• Freshness genuinely does not matter. Overnight reconciliation, daily reporting exports, hourly inventory syncs. If a delay of minutes or hours is perfectly acceptable, a scheduled poll is simpler to build, simpler to operate and simpler to reason about than standing up webhook infrastructure.
• You need to control the intake rate. When the downstream system is fragile or rate-limited, polling lets you pull work at a pace you choose. A webhook storm during a bulk update can overwhelm a consumer that a steady poll would have fed comfortably.
• Reliability through simplicity matters most. Polling is naturally self healing. If one poll fails, the next one picks up everything that changed in between, because the query is always "what changed since my marker." There is no lost-message problem to engineer around, which for some teams is worth more than efficiency.
• The change rate is low relative to the freshness need. If data changes rarely and you only check occasionally, polling's waste is negligible and its simplicity wins outright.

The honest summary is that polling trades efficiency for simplicity and robustness, and there are many integrations where that is precisely the trade you want to make. Do not let the fashionability of webhooks talk you out of a poll that would have been perfectly adequate and half the work.

7. When webhooks win

Webhooks earn their extra operational weight in a well-defined set of situations, and recognising them is the flip side of the polling judgement above.

• Freshness is the whole point. Payment confirmations, fraud alerts, a status a user is watching update on screen, a downstream automation that must react at once. Whenever the value of the information decays quickly, the near-instant delivery of a webhook is worth the infrastructure it demands.
• Events are infrequent but individually important. A system that changes a handful of times a day but where each change matters is the ideal webhook case. Polling it frequently enough to stay fresh would waste thousands of requests to catch a handful of events; a webhook catches each one the moment it happens with zero idle traffic.
• You are integrating at scale across many sources. When you consume changes from thousands of accounts or records, polling each one independently is untenable. Push lets the producers notify you only about the ones that actually changed, collapsing an impossible poll volume into a manageable event stream.
• The producer supports and recommends it. Modern platforms, payment processors, source-control services, messaging and CRM systems, expose webhooks as a first-class feature precisely because they do not want to field endless polling traffic. When the producer is built for push, using it is the path of least resistance for both sides.

The catch you must design for is delivery failure. Because the producer pushes, a message can be lost if your endpoint is down or slow when it fires. Serious webhook integrations pair the push with two safeguards: the producer retries failed deliveries on a backoff schedule, and the consumer keeps a periodic reconciliation poll as a safety net to catch anything the push stream missed. That belt-and-braces design is the mature pattern, and it leads naturally into the hybrid approaches below. Webhooks are also close cousins of the publish-subscribe model, so the pub/sub explainer is a useful companion for anyone building event-driven flows.

8. Long polling and hybrid approaches

The real world is rarely a clean choice between the two extremes, and several intermediate patterns exist precisely to soften the trade-off. It is worth knowing them, because the best production designs often blend rather than pick.

Long polling is the most important middle ground. Instead of the producer answering "nothing new" immediately and forcing the consumer to ask again in a moment, the producer holds the request open, waiting, and only responds when there is genuinely something to return, or when a timeout is reached. From the consumer's side it still looks like polling, a request that eventually returns data, but the constant stream of empty answers largely disappears, and latency drops close to real time because the response is released the instant the event occurs. Long polling gives much of the freshness of a webhook without requiring the consumer to run an inbound public endpoint, which is why it underpins many chat and notification systems.

The webhook-plus-reconciliation hybrid is the pattern I recommend most often for important data. You take webhooks for their speed and treat them as the primary, low-latency path, and you run an infrequent poll, perhaps once an hour or once a day, as a reconciliation sweep that catches anything the push stream dropped. You get real-time reaction in the normal case and self-healing completeness as a backstop. It costs a little more to build than either pattern alone, but for data where both freshness and completeness matter, it is the design that lets you sleep at night.

Beyond these, streaming connections such as server-sent events and WebSockets push a continuous flow of updates over a single long-lived connection, and message queues and pub/sub brokers decouple producers from consumers entirely so that neither has to know about the other's availability. These belong to the same family of ideas: shift the initiative toward the producer, and stop paying for the endless "anything new?" question. Many enterprise platforms expose several of these at once. Microsoft Dynamics 365 Business Central, for example, offers both polling-friendly OData APIs and push-style webhook notifications, and the right integration often uses each where it fits, as covered in the Business Central APIs and integrations guide.

9. References

The patterns described here are well established across the industry. For authoritative and vendor-neutral background, the following are worth reading directly:

• MDN Web Docs, "HTTP" and "Using server-sent events". Foundational reference for request-response and push mechanics on the web.
• RFC 6202, "Known Issues and Best Practices for the Use of Long Polling and Streaming in Bidirectional HTTP". The standards-track discussion of long polling and its trade-offs.
• Stripe, GitHub and Twilio developer documentation on webhooks. Widely cited practical references for signature verification, retries and reconciliation patterns.
• Microsoft Learn, "Business Central API and webhook notifications". A concrete example of one platform exposing both polling and push interfaces.
• Roy Fielding's dissertation, "Architectural Styles and the Design of Network-based Software Architectures". The origin of REST, the request-response style that polling sits on top of.

Final thoughts

Polling and webhooks are not a matter of old versus new or bad versus good. They are two answers to the same question, each with a shape of cost and benefit that suits different jobs. Polling puts the consumer in control, is trivially simple to build, and heals itself when things go wrong, at the price of wasted requests and built-in latency. Webhooks put the producer in control, deliver near-instantly and waste nothing, at the price of always-on infrastructure and the need to handle failed deliveries. Everything else flows from that one decision about who starts the conversation.

The practitioner's habit worth forming is to reach for the simplest pattern that meets the freshness requirement, and no simpler. If minutes of delay are fine and the change rate is low, poll, and do not apologise for it. If the information decays in seconds, if events are important and infrequent, or if you are integrating at a scale where per-record polling collapses, take the webhook and build the reconciliation safety net alongside it. And when the two extremes both pinch, remember that long polling and the webhook-plus-reconciliation hybrid exist precisely to give you most of both. Choose deliberately, size the poll interval or the retry policy to the real requirement, and the timing layer of your integration will quietly do its job instead of becoming the thing that wakes you at night.

Related reading: Enterprise system integration explained, API vs webhook, REST API explained, What is pub/sub, Business Central APIs and integrations.