Webhooks vs. Polling vs. Batch Sync: Choosing the Right Integration Pattern

When two systems need to stay in sync — your ecommerce platform and your inventory system, your CRM and your accounting software — there are really only three ways to move data between them. Most integration problems trace back to picking the wrong one of these three, not to a bug in the implementation.

The three patterns

Webhooks — the source system pushes an event to you the moment something happens. A payment succeeds, an order ships, a record updates — the system that owns that event notifies you in near real time.

Polling — you periodically ask the other system "anything new since I last checked?" On a schedule (every minute, every hour), you query for changes and process what's new.

Batch sync — on a fixed schedule (nightly, weekly), you pull or push a full or partial dataset, reconciling both sides in one pass rather than reacting to individual events.

When webhooks are the right choice

Webhooks are the right default when you need near-real-time reaction to events — a customer support ticket that should trigger an immediate Slack alert, a payment that should immediately update order status, a form submission that should kick off a workflow right away.

The tradeoff: webhooks require your system to be reliably available to receive them, and you're dependent on the sending system's retry behavior if your endpoint is briefly down. A dropped webhook with no retry logic on either side is a silent failure — the data never arrives, and nothing tells you it's missing.

What a reliable webhook implementation actually requires:

• Idempotency handling, so a webhook delivered twice (which happens more often than people expect) doesn't create duplicate records
• A dead-letter queue or equivalent, so failed processing doesn't just vanish
• Signature verification, so you're not processing forged requests
• A reconciliation fallback — some way to catch what a dropped webhook missed, because "the sender guarantees delivery" is rarely actually true

When polling is the right choice

Polling makes sense when the source system doesn't support webhooks, when near-real-time isn't actually required, or when you specifically want control over your own request rate rather than being at the mercy of however fast the other system fires events.

The tradeoff is a direct one: tighter polling intervals mean fresher data and more API calls (and more risk of hitting rate limits); looser intervals mean less load but staler data. Most polling failures come from picking an interval that doesn't match the actual business need — polling every minute for data that only matters daily, or polling hourly for something that needed to be near-instant.

When batch sync is the right choice

Batch sync is underrated. For a lot of business integrations — nightly inventory reconciliation, weekly financial reporting exports, daily CRM-to-data-warehouse syncs — real-time delivery adds complexity without adding real value. Nobody's waiting on the data between midnight syncs.

Batch sync is also the most forgiving pattern operationally. A failed nightly job can simply retry the next night, or be re-run manually, without the cascading complexity of catching up on a backlog of missed real-time events.

The tradeoff: it's the wrong pattern the moment "eventually consistent, once a day" isn't good enough for the business process depending on it.

The mistake most integrations actually make

Teams often default to whichever pattern is easiest to implement rather than the one that matches the actual business requirement. A common failure mode: building a real-time webhook integration for a workflow that genuinely only needed daily batch sync, and then spending significant engineering time on reliability problems (retries, idempotency, dead-letter handling) that a much simpler batch job would never have needed in the first place.

The reverse mistake happens too — using nightly batch sync for something that actually needed to be near-instant, and then getting support tickets about "stale data" that are really a symptom of the wrong integration pattern, not a bug.

How to actually decide

Ask what the business impact of delay actually is, specifically:

• If a five-minute delay causes real harm (a customer sees the wrong order status, a payment fails silently) — webhooks, with proper reliability handling.
• If the data needs to be reasonably fresh but a few minutes of lag is fine, and the source system doesn't support webhooks — polling, at an interval matched to actual need.
• If "as of last night" is genuinely good enough — batch sync, which is simpler to build, easier to debug, and more forgiving when something goes wrong.

Most integration reliability problems we get called in to fix aren't bugs in the code — they're the wrong pattern applied to the actual business requirement, with the implementation faithfully doing what it was built to do.