Define the integration requirements before choosing a mechanism
All three approaches can carry a change from system A to system B. The important differences are how quickly they deliver it, what happens during an outage, and who controls the flow. Start by defining acceptable latency, whether a missed update is recoverable, whether changes must be processed in order, how bursty the workload is, and what interfaces the source actually supports. Without those answers, teams often build an event platform for a modest synchronization job or choose a simple poller that cannot meet the recovery requirements.
It also helps to separate notification from data delivery. A webhook may only announce that a resource changed, leaving the receiver to fetch its current state. A poller reads state directly. A stream event often carries enough information for downstream processing. That distinction affects exposure of sensitive data, auditability, source-system load, and what can be replayed later.
Use webhooks for responsive integrations with controlled delivery
Webhooks are a strong default when the source natively emits notifications, event volume is moderate, and the business expects a response within seconds. Typical examples include starting an ERP workflow after a CRM opportunity changes or invoking an enterprise assistant when a LINE message arrives. The source sends traffic only when something happens, so the normal execution path is direct and relatively easy to understand.
The HTTP endpoint is the easy part. A production receiver should verify signatures and timestamps, acknowledge quickly, and place the work on an internal queue instead of completing every database write and external API call inside the request. Each notification needs a stable event identifier, and handlers must be idempotent. A timeout can cause the sender to retry a request that the receiver already processed successfully.
Do not assume delivery order. An older event that arrives late must not overwrite a newer state, so compare source versions, sequence numbers, or update timestamps when available. Also inspect the provider's retry policy, retention period, and event-history API. If the source offers no retry or recovery mechanism, use a periodic reconciliation job rather than treating the webhook as the only record of change.
Use polling when compatibility and control matter most
Polling is often the practical answer for older ERP systems, government platforms, and SaaS APIs without dependable notifications. The reader controls the schedule, can pause safely, and can resume from a known cursor without exposing a public callback endpoint. For daily batches, periodic inventory checks, and workflows that tolerate several minutes of delay, a poller can be substantially easier to operate than streaming infrastructure.
A reliable poller should not repeatedly scan the entire source. Prefer an incremental identifier, update timestamp, change version, or pagination cursor, and persist the checkpoint only after a batch is safely committed. Query with a small overlap window to cover clock differences, timestamp precision, and late commits. Because overlap creates duplicates, writes still need idempotent keys. Conditional requests, ETags, and dedicated delta endpoints can further reduce bandwidth and source load.
Polling frequency should adapt to conditions. Back off with jitter after rate limits and transient failures; increase batch size or frequency carefully when a backlog develops. Monitor business freshness, not just HTTP success. A poller can return successful responses for hours while its cursor remains stuck on malformed data, so alert on checkpoint age, repeated records, and the gap between the newest source item and the newest locally applied item.
Use event streams for multiple consumers, buffering, and replay
Event streams become valuable when the same events feed several independent services, traffic is continuous or bursty, and retention or replay has clear business value. An order event might be consumed separately by inventory, notifications, analytics, and risk services. Each consumer tracks its own progress, while the broker separates producer speed from consumer speed and buffers events during a downstream outage.
That flexibility introduces operational work. The team must choose partition keys because ordering is generally guaranteed only within a partition. It must also manage consumer groups, retention, access controls, schema evolution, lag, retries, and dead-letter handling. Claims of exactly-once processing do not automatically cover database updates or calls to external APIs. Consumers commonly still need idempotency keys, a transactional inbox, or an equivalent consistency pattern.
Design events as durable facts, with an event ID, source, occurrence time, entity ID, and schema version. Additive schema changes should remain backward compatible, while breaking changes need an explicit version and migration window. Without contract ownership and observability, a stream merely replaces visible point-to-point dependencies with harder-to-trace data dependencies.
Combine mechanisms around delivery and recovery paths
Most enterprise integrations do not require a pure choice. A webhook can provide fast notification while a scheduled poller reconciles missed changes. External webhooks can enter an internal queue and be converted into a governed event format. A stream can distribute real-time changes while a batch process rebuilds authoritative snapshots. The useful design question is often which mechanism serves the fast path and which one guarantees recovery.
- Choose webhooks when the source provides dependable notifications, latency must be low, the receiver can expose a secure endpoint, and retries or event lookup are available.
- Choose polling when the source is limited, some delay is acceptable, or the integration team needs direct control over pacing and backfills.
- Choose event streams when sustained event flow, independent consumers, buffering, retention, and replay justify the additional platform work.
- Choose a hybrid when real-time notification is not fully trustworthy, external and internal integration patterns differ, or low latency must coexist with verifiable eventual consistency.
Whichever mechanism you adopt, define event identity, idempotency, retry limits, dead-letter handling, backfill procedures, and alert ownership before launch. The goal is not to select the most sophisticated technology. It is to build an integration path that remains observable, recoverable, and maintainable within the real constraints of the source systems and the engineering team.