Webhook Delivery vs. Message Queues: When to Use What

“Why not just use Kafka?” It’s a fair question, and it comes up almost every time webhooks get proposed for event delivery. Message queues and webhooks both move events from a producer to a consumer, so at a glance they seem interchangeable. In practice they solve different problems and behave very differently once real traffic hits them.

This post covers when each one fits, and why plenty of systems end up running both.

The Core Difference

The distinction that matters most is who owns the consumer.

A message queue moves events between systems you control. You run the producer, you run the consumer, and you run or manage the broker sitting between them. A webhook moves events to a system you don’t control. You produce the event, but the consumer is somebody else’s server, whether that’s a customer, a partner, or a third-party integration you’ve never seen.

Almost every other difference follows from that one.

How Message Queues Work

A message queue puts a broker between the producer and the consumer.

Producer -> Broker (SQS, Kafka, RabbitMQ) -> Consumer

The producer writes messages to the broker. The consumer pulls them back out at its own pace. The broker owns persistence, ordering, and whatever delivery guarantees the system promises.

A few things fall out of that design. Delivery is pull-based, so the consumer decides when to read and how fast. Messages live in the broker until something consumes them, and the consumer sets its own throughput, processing at whatever rate it can manage. Both sides need to reach the same broker, which means shared network access and shared credentials.

How Webhooks Work

Webhooks skip the broker. The producer sends an HTTP request straight to the consumer.

Producer -> HTTP POST -> Consumer's endpoint

There’s nothing in the middle unless you put it there, which is more or less what Hookbridge is. The producer pushes each event to the consumer’s URL and moves on.

The trade-offs invert. Delivery is push-based: the producer decides when to send, and the consumer has to be ready to receive. There’s no shared infrastructure to set up, just a publicly reachable HTTP endpoint. The protocol is plain HTTP, so no special client library or broker connection is involved. The consumer can’t control the pace either, since events show up whenever the producer sends them.

When to Use Message Queues

Reach for a message queue when the situation looks like one of these.

You own both sides

If you’re wiring together microservices inside your own infrastructure, a queue is almost always the better choice. You control the producer, the consumer, and the broker, so you can guarantee connectivity, plan capacity, and tune every side.

Order Service -> SQS -> Payment Service -> SQS -> Notification Service

You need strict ordering

Kafka and similar systems guarantee ordering within a partition. If events for a given entity have to be processed in exact sequence, a partitioned queue is built for that. Getting the same guarantee out of webhooks takes real work.

The consumer needs to set its own pace

When a consumer does heavy work per message, it needs to pull at its own rate: slow down when it’s busy, catch up when it has room. A pull model gives it that control. Webhooks deliver whether the consumer is ready or not.

You’re moving huge internal volume

Pushing millions of events per second between internal services is exactly what Kafka was built for. At that volume the per-request overhead of HTTP, connection setup, TLS handshakes, header parsing, makes webhooks a poor fit for internal traffic.

You need rich routing

Fan-out to many consumers, content-based routing, priority lanes, delayed delivery: brokers ship with all of these. Rebuilding them on top of webhooks means building a lot of infrastructure yourself.

When to Use Webhooks

The consumer is external

This is the main case. If you run an API and your customers need to know when something happens in their account, webhooks are the standard answer. You can’t hand every customer a connection to your Kafka cluster.

Your API -> webhook -> Customer's server

Stripe, GitHub, Twilio, and Shopify all deliver webhooks for the same reason: their consumers are systems they don’t run.

The consumer should need almost nothing

A webhook asks the consumer for one thing: an HTTP endpoint. No client library, no broker connection, no subscription management. Most web frameworks can receive one in a handful of lines.

Consuming from a queue asks for a lot more: broker credentials, a client library for that specific broker, configuration for consumer groups and offsets and acknowledgements, and network access to the broker, which often means a VPN or VPC peering.

You want to stay technology-agnostic

Webhooks run on HTTP, which every stack already speaks. The consumer can be written in any language and deployed anywhere, and it never has to know what the producer runs. A queue ties both ends to one technology: pick Kafka and your consumers need a Kafka client; switch to RabbitMQ and every consumer changes with you.

You want events pushed in real time

Webhooks arrive the moment the event happens. No polling interval, no batch window, no consumer lag. When latency actually matters, as it does for payment notifications, security alerts, and deployment triggers, push beats pull.

The Hybrid Approach

Most real systems don’t pick a side. A common shape looks like this: an event happens, you write it to an internal queue, and two different kinds of consumer read from there.

Event occurs in your application
         |
         v
Write to internal queue (SQS/Kafka)
         |
    +----+----+
    |         |
    v         v
Internal    Webhook delivery
consumers   service
    |         |
    v         v
Your own    External
services    consumers

The queue handles internal distribution. A webhook delivery service reads from the same queue and takes care of external delivery, along with the retries, backoff, signatures, and observability that external endpoints demand.

Internal services get the throughput and ordering a queue provides. External consumers get an integration that’s easy to stand up. And event production stays decoupled from both, so neither side constrains the other.

Comparison Table

Common Misconceptions

“Webhooks aren’t reliable”

They can be every bit as reliable as a queue when they’re built well. Retries, backoff, dead letter queues: these are the same ideas applied to HTTP. What’s genuinely harder is that you don’t control the consumer, so reliability becomes a shared responsibility rather than something you can guarantee end to end.

“A queue is always the better way to deliver events”

For internal delivery, often yes. For external integrations, it isn’t even an option. You can’t ask every customer to run a Kafka consumer or open a connection to your RabbitMQ cluster.

“You have to pick one”

You don’t. Queues internally, webhooks externally. They fit together without much friction.

Where Hookbridge Fits

In the hybrid setup above, Hookbridge is the webhook delivery service. We handle the external side: taking events out of your system and getting them to your customers’ endpoints reliably, with retries, signatures, observability, and the operational machinery that comes with it.

Keep your internal queues for your internal services. We’ll handle the awkward part, pushing events to endpoints you don’t control and can’t fix when they break. Hookbridge does that so you don’t have to build it again.

Next up: How to Evaluate a Webhook Delivery Service. A practical framework for comparing webhook delivery services, and the pricing traps to watch for.