Webhooks vs. Kafka
When building modern apps, it’s important to be able to handle real-time data. It’s becoming a trend to shift towards using Webhooks or Apache Kafka.
As APIs become more widespread, developers are now looking to receive real-time event data from their API providers. The most common solution for this is webhooks, though this can also be achieved using Kafka.
Which one should you use? It depends.
This guide will help you understand the differences between these two options so you can choose the best one for your needs.
Webhooks vs Kafka at a glance
| Webhooks | Kafka | |
|---|---|---|
| Transport | HTTP POST to a URL the receiver registers | Consumers pull from a partitioned log over TCP |
| Who runs the receiver | Someone else, usually a customer or partner | You, inside your own infrastructure |
| Delivery | At-least-once through retries with backoff | At-least-once through consumer offsets and replay |
| Ordering | Not guaranteed across retries | Guaranteed within a partition |
| Fits best | Many endpoints with varied volumes | Very high throughput to a few consumers |
| What you operate | An HTTP endpoint and a signature check | Brokers, partitions, consumer groups, retention |
What is a Webhook?
A webhook is a reverse API, or server to server push notification. They work by sending out an HTTP request to a specified endpoint when an event is triggered. This makes webhooks ideal for integrating two applications.
If you’re not familiar with webhooks, you can learn more about them in this article: What is a webhook?
Examples:
An e-commerce site sending order updates and shipment tracking to a large number of merchants with varying order volumes is a prime scenario for webhooks. Their flexible, event-driven model allows minimal effort from each merchant.
Likewise, a news site providing article updates to publishers with fluctuating subscriber bases can meet the variable delivery needs using webhooks without overburdening any single publisher.
What is Kafka?
Apache Kafka is an open-source distributed event streaming platform most commonly used for high-performance data pipelines, streaming analytics, and data integration.
Because of the above, Kafka is quite suitable for processing events between services, similar to webhooks.
Examples:
An online streaming service constantly sending video data to millions of mobile app users, where only a few thousand receive the stream simultaneously, is a good use case for Kafka’s efficient high-volume delivery.
Similarly, a social network broadcasting live video feeds can use Kafka to handle the high throughput needed for many followers watching the same feed.
Comparing Webhooks and Kafka
Message Volume
Kafka is preferable for constant, high-volume message streams to a limited audience. However, its architecture imposes greater complexity and resource demands.
Webhooks are better suited for varied message volumes sent to a diverse audience.
Flexibility and Ease of use
Webhooks: HTTP-based, simplify integration and reduce operational overhead, making them more flexible and user-friendly.
Kafka: requires more effort and expertise to set up and maintain.
Operational Burden
Kafka’s setup and maintenance require substantial effort and expertise, potentially posing challenges for self-serve scenarios.
Webhooks offer a more accessible solution with lower maintenance requirements.
Integration Simplicity: Webhooks are generally considered easier to integrate with other systems than Kafka, owing to their straightforward HTTP callback mechanism.
Learning Curve: Webhooks are simpler to understand and use, making them more accessible for beginners or for simpler applications. Kafka’s advanced features and distributed system principles require a steeper learning curve.
Operational Complexity: Kafka is higher due to the features designed for large-scale operations, which, while powerful, introduce more complexity.
Scalability: Kafka excels in scalability, capable of handling very high volumes of data efficiently, which is a key advantage over webhooks.
Fault Tolerance: Kafka also has high fault tolerance, benefiting from features like replication and partitioning to ensure data integrity and availability.
Which one should you use?
It depends.
Kafka is a more powerful and scalable solution than webhooks, but it comes with greater complexity and operational overhead. Webhooks are a simpler and more user-friendly solution, but they may not be suitable for high-volume message streams.
Kafka or a webhook service for webhook ingestion?
Kafka cannot receive a webhook on its own. A provider such as Stripe or GitHub sends an HTTP POST to a public URL, so something must accept that request, verify its signature, return a 2xx before the provider’s timeout, and only then publish the event to a topic. A webhook ingestion service such as Svix Ingest does that front half, with storage and replay, and can forward verified events into Kafka. Use both when your consumers already read from Kafka; use the ingestion service alone when they do not. When the consumers are a handful of your own HTTP services rather than Kafka readers, a queue per destination does the same job, as in how to fan out webhooks to multiple services.