Webhooks vs Polling vs Event-Driven Integrations
A comprehensive technical comparison of data synchronization patterns: HTTP polling, outbound webhooks, and real-time event streaming architectures.
When synchronizing state between business systems—such as propagating an order from an e-commerce platform to an ERP, or alerting a mobile app of a verified payment—choosing the communication pattern determines network efficiency, infrastructure cost, and data freshness.
The three primary integration mechanisms are Periodic Polling, Outbound Webhooks (Push), and Event-Driven Streaming (Pub/Sub).
POLLING (Pull):
Consumer --- [GET /api/orders?since=12:00] ---> Provider (Returns 0 results)
Consumer --- [GET /api/orders?since=12:05] ---> Provider (Returns 0 results)
Consumer --- [GET /api/orders?since=12:10] ---> Provider (Returns 1 new order)
WEBHOOKS (Push):
Provider (Order Created) --- [POST https://consumer.com/webhook] ---> Consumer
EVENT STREAMING (Pub/Sub):
Publisher ---> [Kafka / RabbitMQ Topic: "orders.created"] ---> Multiple Consumers
Architectural Comparison Matrix#
| Dimension | Short Polling | Outbound Webhooks | Event-Driven Streaming |
|---|---|---|---|
| Latency | High (Average: half poll interval) | Low (< 500ms from event) | Real-time (< 10ms) |
| Server Resource Overhead | Severe (99% of requests return empty) | Low (Only fires on actual state change) | Highly optimized / Persistent socket |
| Security Mechanism | Outbound API Token | HMAC-SHA256 Signature Header | TLS Mutual Auth / SASL |
| Consumer Endpoint Required? | No (client initiates outbound call) | Yes (must expose public HTTPS URL) | No (pull from consumer group) |
| Ordering & Replay | Sequential based on timestamp | Out-of-order possible; requires DLQ | Guaranteed partition order & offset replay |
1. The True Cost of Polling#
While polling is straightforward to implement, it incurs massive waste at scale. A system polling 10,000 partner records every 60 seconds generates 14.4 million HTTP requests per day, even if only 20 records changed. This exhausts database connections and triggers unnecessary compute costs.
2. Engineering Outbound Webhooks for Enterprise Reliability#
Outbound webhooks deliver immediate notifications but introduce distributed failure risks. A robust webhook engine must implement:
- Cryptographic Signatures: Attaching an
X-Signature-SHA256computed from the payload and shared secret to prevent spoofing. - Timestamp Nonces: Including
X-Timestampto prevent replay attacks. - Exponential Backoff with Jitter: Retrying failed HTTP 5xx responses over a 24-hour window (e.g. at 1m, 5m, 30m, 2h, 8h).
- Dead-Letter Queues (DLQ): Allowing administrators to manually inspect permanently failed webhook deliveries and replay them after endpoint fixes.
// Dispatching signed webhook in Alegor Integrations Module
class WebhookDispatcher
{
public function dispatch(WebhookEndpoint $endpoint, string $event, array $payload): void
{
$timestamp = time();
$jsonPayload = json_encode([
'id' => Str::uuid()->toString(),
'event' => $event,
'timestamp' => $timestamp,
'data' => $payload,
]);
$signature = hash_hmac('sha256', "{$timestamp}.{$jsonPayload}", $endpoint->secret);
Http::timeout(5)
->withHeaders([
'Content-Type' => 'application/json',
'X-Alegor-Signature' => $signature,
'X-Alegor-Timestamp' => (string) $timestamp,
'User-Agent' => 'Alegor-Webhook-Engine/2.0',
])
->post($endpoint->url, json_decode($jsonPayload, true));
}
}
3. When to Use Event Streaming (Kafka / RabbitMQ)#
Webhooks are ideal for B2B external integrations where partners manage their own web servers. For internal, high-throughput microservices or asynchronous micro-tasks within your own infrastructure, internal event brokers (RabbitMQ / Redis Streams / Kafka) provide higher throughput, exactly-once delivery guarantees, and backpressure management without HTTP overhead.
Explore the Alegor Integrations Module or read How to Design Reliable Integrations.
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