Confluent Kafka Alternatives for Event-Driven Applications: Comparing Hookdeck Event Gateway, Amazon EventBridge, Azure Event Grid, and Google Eventarc
Kafka is one of the big players of the event-driven world. Not only can Kafka get your events from source to destination but, thanks to its rich ecosystem, it offers complex in-flight processing, a SQL interface, and ready-made integrations.
But that power comes at a price. Kafka is complex. Set-up, operations, and development each divert resources away from delivering the functionality you want to build. Managed Kafka offerings, like that from Confluent, take care of some of the operational side. But there's no getting away from the fact that choosing Kafka means carving out time and budget that could be used elsewhere.
In this article, we'll look at some of the alternatives to Confluent Kafka that might allow you to keep your focus on building your application rather than managing infrastructure. Specially, we'll compare Confluent's managed Kafka with:
- Hookdeck Event Gateway: the complete event gateway solution with 120+ pre-configured sources.
- Amazon EventBridge: a point-to-point event bus with minimal in-flight processing.
- Azure Event Grid: a pub-sub messaging tool that can ingest from MQTT and data sources.
- Google Eventarc: a point-to-point event tool tightly integrated with Google Cloud. Eventarc Advanced adds routing, filtering, transformation, and external HTTP delivery.
Let's start by looking at what Confluent Kafka offers and the criteria we'll use to compare with its alternatives.
Comparing Confluent Kafka alternatives
Decoupling the components in your application architecture can make scaling, maintenance, and resilience easier to achieve. But an event-driven architecture is only as good as your event gateway tools.
Comparing the options available can be hard, though, as each event gateway takes a somewhat different approach to the problem. That's why we'll compare these Confluent Kafka for EDA alternatives using a standard set of criteria:
- Does it integrate with the consumers and producers you need? Can it easily work with the tools you already use? How easy is it to add new integrations?
- Can it process events? Does it offer in-flight enrichment and transformations?
- What storage options does it offer? Can you store and replay events or do you need to integrate with another tool?
- How does it handle auth? What are the tools and methods that the event gateway tool uses to authenticate and sign events?
- What options does it offer for observability? Can you monitor your events and the overall health of your gateway using the tool itself or do you need to work with external tools?
- What impact does it have on developer resources? Will you need to hire specialists to manage and work with the tool or does it slot easily into your existing tech stack?
An overview of Confluent Kafka
For the purposes of this comparison, Kafka comes in two forms: there's the open source Apache Kafka and then managed Confluent Kafka service. Let's start with Apache Kafka.
Apache Kafka
Apache Kafka is an open source project that the Apache organization describes as a distributed event store and stream processing platform. With the release of Apache Kafka 4.0, the platform now runs entirely without ZooKeeper using KRaft mode by default, simplifying cluster management. Kafka 4.0 also introduces Kafka Queues (via share groups) for point-to-point messaging alongside the traditional pub/sub model. That word "distributed" is where a lot of the complexity comes from. Kafka runs as a cluster of multiple nodes. That's great news for scalability: when you need more capacity, add another node and Kafka redistributes the data around the newly enlarged cluster to give you more storage, CPU, and network. Kafka also makes multiple copies of everything, so you can stand to lose one or more parts of the cluster and still keep going.
The data model underlying Kafka is a distributed, append-only log that is divided into topics. When a data producer pushes an event into Kafka, that event gets added to the end of the log and Kafka makes multiple copies around the cluster. Data destinations, or consumers, subscribe to topics in the log, meaning that it is effectively a publish-subscribe system. The result is that Kafka both stores and distributes events.
But a lot of Kafka's value comes from its in-flight processing through Kafka Streams and kSQL. Kafka Streams allows you to write custom data processing code that runs on the Kafka cluster itself. kSQL, as the name suggests, provides a SQL interface for manipulating and querying data in your Kafka cluster.
Confluent Kafka
We've seen what the open source Apache Kafka is all about. So, what does Confluent's managed service bring to the table?
The value of Confluent comes mostly from operating and scaling the Kafka cluster on your behalf. As with any cloud service, that means you don't have to worry about the underlying operating system, networking, resource allocation, performing upgrades to Kafka, and so on. However, and it's a pretty big "however", that doesn't mean that Confluent's version of Kafka is serverless. So, you still need to think about cluster sizing and managing performance, for example.
Confluent Platform 8.0, built on Kafka 4.0, adds Confluent Intelligence (managed AI services including anomaly detection and forecasting), an updated Control Center, and FlinkSQL preview for stream processing alongside kSQL. Confluent also provides proprietary functionality such as advanced monitoring and management tools, proprietary connectors to external tools, a REST proxy for easier integrations, and enhanced security features.
It's difficult to compare Apache Kafka to anything else because it almost sits in a category of its own when it comes to open-source tools. The closest alternatives are all managed or serverless tools. That's why in this comparison we're specifically looking at alternatives to Confluent Kafka rather than Apache Kafka.
Confluent Kafka key features
Before we can look at Kafka alternatives, let's take a look at what Confluent Kafka offers.
- Event pattern: Publish-subscribe, where consumers subscribe to topics.
- Event format: Plain strings, JSON, or Avro.
- Event integrations: The Confluent REST Proxy works with both data sources and data sinks. It provides a RESTful interface to a Kafka cluster, enabling you to produce and consume messages, view cluster metadata, and perform administrative operations using HTTP requests. That makes it easier to integrate with applications that don't have a pre-built Kafka integration.
- Processing: Kafka Streams and kSQL enable complex in-flight processing.
- Storage: Kafka stores all events by default, using the append-only log. You can choose how long Kafka retains events, with available storage being the upper limit.
- Routing: Kafka uses a topic-based publish-subscribe model, with more nuanced routing available by creating custom routing and filtering code in Kafka Streams.
- Observability: Confluent Control Center is a web-based interface for monitoring and managing your hosted Kafka clusters, offering real-time metrics, alerts, and visual dashboards.
- Error management and recovery: Kafka lets you create your own retry and recovery policies, with the option of routing failed events to a dead-letter queue for manual processing.
- Operational impact: Although Confluent's managed service simplifies running Kafka, it isn't an entirely serverless experience. You'll still need to create processes and dedicate resources to monitoring, configuring, and tuning your cluster.
Confluent Kafka advantages
- Comprehensive functionality: Almost everything you could need for building an event-driven application architecture is available from Confluent Kafka.
- Scalability and performance: Kafka is proven at very large scales and with Confluent's serverless-scaling model it'll perform well even under very heavy loads.
- Rich ecosystem: Kafka connects with just about everything, whether directly or through Confluent's HTTP proxy.
- Complex processing: Kafka Streams enables you to perform in-depth processing on events as they pass through the cluster.
Confluent Kafka disadvantages
- Hard to learn: Unlike the alternatives we're considering, Kafka has a steep learning curve. Partly that's thanks to its configurability but it's also due to the fact that even a managed offering cannot shield you from the underlying complexity of Kafka's architecture.
- Complex to run: Even in a managed context, Kafka still requires significant operational expertise and effort to properly configure, monitor, and maintain.
- Potentially costly: That complexity translates into higher costs when it comes to managed services like Confluent. The operational expertise and resourcing that managed services need to deploy to run Kafka results in higher bills.
Confluent Kafka alternatives
If you're not sure you want the complexity or expense of Kafka, what are your options? As we mentioned earlier, we're going to investigate four Kafka alternatives:
- Hookdeck
- Amazon EventBridge
- Azure Event Grid
- Google Eventarc
Let's look in detail at how each one compares to Confluent Kafka.
Hookdeck Event Gateway
Hookdeck Event Gateway takes a very different approach to Kafka in that it is a fully managed, end-to-end gateway solution based around webhooks. If you're building an event-driven architecture, Event Gateway gives you all the benefits of Kafka without the downsides.
Hookdeck Event Gateway key features
- 120+ pre-configured sources: Event Gateway ships with over 120 pre-configured source types that auto-configure authentication, signature verification, and response formatting for providers like Stripe, Shopify, GitHub, and Twilio. No custom integration code required.
- Ingests common data sources: Event Gateway integrates with your infrastructure through webhooks and API calls, allowing it to ingest events from various sources without custom connectors.
- JavaScript-based event processing: With Event Gateway you can write your own JavaScript scripts for in-flight event enrichment and transformation via both a code editor and a visual editor.
- Tunable event retries: Event Gateway provides granular control over event delivery retries. And once Event Gateway hits the retry limit, it sends failed events to a queue for manual processing later.
- Visual event pipeline builder: Event Gateway's user-friendly dashboard simplifies creating and managing event pipelines visually, unlike Confluent Kafka's configuration-based approach.
- Auth and verification: Event Gateway supports HMAC, Basic Auth, Bearer Token, and API key verification for a growing number of services, making it easy to integrate securely with many different tools and systems.
- Observability: Event Gateway provides end-to-end observability with full-text search across your entire event history, visual event traces, an issue tracking system with configurable issue triggers, and metrics export to Datadog, Prometheus, and New Relic.
How does Hookdeck Event Gateway compare to Confluent Kafka?
Both Hookdeck Event Gateway and Confluent Kafka set out to solve similar problems, although in quite different ways. In operational terms, Event Gateway is a fully serverless platform, meaning that you don't have to give any thought to the underlying architecture. Confluent's managed Kafka, on the other hand, shields you from the day to day work of operating Kafka but you still need to consider how Kafka works.
Another area of difference is the simplicity of Event Gateway's integration model. Being HTTP-based means that Hookdeck needs virtually no customization beyond authentication configuration on the data source or data destination sides, whereas integrating with Kafka requires custom adapters. Similarly, Event Gateway's event processing is JavaScript-based, making it accessible to most developers, whereas Kafka Streams is a complex Java-based application framework.
| Feature | Hookdeck Event Gateway | Confluent Kafka |
|---|---|---|
| Simple to set up and manage | ✅ | ❌ |
| Consume external event sources without custom development | ✅ | ✅ Some custom code may be required if a datasource connector does not already exist. |
| Deliver to any HTTP destination | ✅ | ✅ Requires REST API addon |
| Multiple forms of auth | ✅ | ✅ |
| Complex in-flight processing | ✅ | ℹ️ Requires Kafka Streams or kSQL integration |
| Configurable data storage | ✅ | ✅ |
| Error handling and recovery | Configurable retries for up to 30 days, depending on plan, as well as rate limiting | Highly configurable, limited by available storage |
| Built-in observability tooling | ✅ | ✅ |
Amazon EventBridge
The remaining three alternatives to Confluent Kafka that we're considering are all specific to one of the major public cloud providers. EventBridge is Amazon's offering and it comes in three parts:
- Event Bus: Point-to-point routing between multiple sources and destinations, with lightweight in-flight text processing.
- Pipes: For ETL-like workloads, deals in fixed connections between sources and destinations, with more sophisticated in-flight processing.
- Scheduler: For cron-like timed event delivery.
Read the Amazon EventBridge alternatives guide.
Amazon EventBridge key features
- Point-to-point connections: Set-up rules that route events from source to destination according to their contents and metadata.
- Event format: EventBridge has its own event format, meaning you'll need to convert from the source format.
- Event sources: EventBridge largely favors the AWS ecosystem when it comes to integrations with data sources. However, Amazon offers a number of partner integrations, as well as the PutEvents API, Java SDK, and CLI, which allow you to create custom integrations with external data producers.
- Event destinations: EventBridge supports webhooks and third-party APIs, as well as delivery to AWS products.
- In-flight text processing: Simple in-flight text processing is available but more complex processing requires secondary tools, such as your own Lambda functions.
- Persistence: EventBridge stores failed events for retrying and also provides event archival storage.
How does Amazon EventBridge compare to Confluent Kafka?
The big differences between EventBridge and Confluent Kafka all stem from EventBridge's relative simplicity. There's much less to learn and, as a serverless product, less to configure or manage. However, of course, the trade-off is that EventBridge offers less functionality, notably when it comes to in-flight processing.
| Feature | Amazon EventBridge | Confluent Kafka |
|---|---|---|
| Simple to set up and manage | ℹ️ Requires custom development to integrate all but a short list of external data sources and processing tools | ❌ |
| Consume external event sources without custom development | ✅ | ✅ Some custom code may be required if a datasource connector does not already exist. |
| Deliver to any HTTP destination | ✅ | ✅ Requires REST API addon |
| Multiple forms of auth | ❌ | ✅ |
| Complex in-flight processing | ❌ | ℹ️ Requires Kafka Streams or kSQL integration |
| Configurable data storage | ❌ | ✅ |
| Error handling and recovery | Retries for up to 24 hours, followed by dead letter queue | Highly configurable, limited by available storage |
| Built-in observability tooling | ℹ️ Integration with Amazon CloudWatch | ✅ |
Azure Event Grid
Azure Event Grid is the Azure ecosystem's event gateway tool and it offers just a fraction of the functionality of Kafka. However, that's almost the point. Event Grid is designed to get events from one place to another and not much else.
Like Kafka, Event Grid uses the pub-sub model, where event producers publish to named topics and consumers subscribe to those topics. But that's where the similarities end. Event Grid's MQTT and HTTP webhook interfaces mean it could be easier to integrate new data sources than with Kafka, but its lack of in-flight processing marks Event Grid as a tool only for moving events.
Read the Azure Event Grid alternatives guide.
Azure Event Grid key features
Pub-sub: As your event-driven architecture grows, working with more integrations and a higher volume of events, Event Grid's pub-sub model offers scalability advantages over something like Amazon EventBridge. By decoupling event producers from event consumers, Event Grid enables independent scaling of producers and consumers, just like Kafka but without the associated complexity of Kafka.
Works with MQTT and webhook data sources: Event Grid integrates directly with products from the Azure ecosystem, as well as external data sources through the MQTT protocol and HTTP webhooks. Event Grid's MQTT broker capabilities have expanded significantly, with support for MQTT, WebSocket transport, custom domains, client lifecycle events, retained messages, and Microsoft Entra JWT authentication. Support for the CNCF CloudEvents standard might make integration simpler, if data sources and destinations also support it.
No in-flight transformations: To enrich and transform events, you'll need to send them out of Event Grid and into another tool, such as your own custom code.
No storage option: Other than storing events to enable retries, Event Grid will make you look elsewhere for event storage.
How does Azure Event Grid compare to Confluent Kafka?
Kafka sets out to be a comprehensive event streaming and processing platform, whereas Event Grid just wants to move events around your system. If you have no or little need for in-flight transformations then Event Grid could offer a simpler solution.
| Feature | Azure Event Grid | Confluent Kafka |
|---|---|---|
| Simple to set up and manage | ✅ | ❌ |
| Consume external event sources without custom development | ✅ | ✅ Some custom code may be required if a datasource connector does not already exist. |
| Deliver to any HTTP destination | ✅ | ✅ Requires REST API addon |
| Multiple forms of auth | ✅ | ✅ |
| Complex in-flight processing | ✅ | ℹ️ Requires Kafka Streams or kSQL integration |
| Configurable data storage | ❌ | ✅ |
| Error handling and recovery | Retries for up to 24 hours, followed by dead letter topic | Highly configurable, limited by available storage |
| Built-in observability tooling | ℹ️ Integration with Azure Dashboard | ✅ |
Google Eventarc
Google Eventarc comes in two tiers: Eventarc Standard and Eventarc Advanced. Standard is tightly coupled to the Google Cloud ecosystem with point-to-point event delivery and no in-flight processing. Eventarc Advanced significantly expands Eventarc's capabilities with message routing, filtering, transformation, and delivery between services — including external HTTP endpoints. Both tiers work with the CNCF's CloudEvents format.
Read the Google Eventarc alternatives guide.
Google Eventarc key features
- Focus on Google Cloud integrations: Eventarc Standard integrates primarily with other Google Cloud products. Eventarc Advanced broadens this with support for routing events between Google Cloud services and external HTTP endpoints.
- Processing (Advanced only): Eventarc Advanced supports message transformation and enrichment pipelines. With Eventarc Standard, you must route events to another tool, such as a Google Cloud Function, for any processing.
- External delivery (Advanced only): Eventarc Advanced can deliver events to external HTTP destinations. With Standard, you'd need to bring in another tool, such as GCP Pub/Sub or a Cloud Function, to handle delivery outside the Google ecosystem.
How does Google Eventarc compare to Confluent Kafka?
The comparison depends on which Eventarc tier you use. Eventarc Standard's limited scope makes it tough to compare with Confluent Kafka — it can't send events to external destinations and has no processing capabilities. Eventarc Advanced closes many of these gaps with routing, filtering, transformation, and external HTTP delivery, but Kafka still offers significantly deeper processing and storage capabilities.
| Feature | Google Eventarc | Confluent Kafka |
|---|---|---|
| Simple to set up and manage | ℹ️ Requires integrations with other tooling to achieve full event gateway functionality | ❌ |
| Consume external event sources without custom development | ✅ | ✅ Some custom code may be required if a datasource connector does not already exist. |
| Deliver to any HTTP destination | ℹ️ Eventarc Advanced only | ✅ Requires REST API addon |
| Multiple forms of auth | ❌ | ✅ |
| Complex in-flight processing | ℹ️ Eventarc Advanced only | ℹ️ Requires Kafka Streams or kSQL integration |
| Configurable data storage | ❌ | ✅ |
| Error handling and recovery | Retries for up to 24 hours, followed by dead letter topic | Highly configurable, limited by available storage |
| Built-in observability tooling | ❌ | ✅ |
Summarizing Confluent Kafka's alternatives
The tools you choose will have a long-term impact on your budget, your ability to bring functionality to market, and the skills you need on your team.
All flavors of Kafka come with a lifelong burden of operational and development complexity in exchange for its power. But if you're not willing to make the functionality trade-offs demanded by Amazon EventBridge, Azure Event Grid, and Google Eventarc — even with Eventarc Advanced's expanded capabilities — does that mean Kafka's your only option? Well, no.
Hookdeck Event Gateway gives you the flexibility to put events at the heart of your application's architecture but with a truly serverless operational model and developer-friendly touches such as webhook-based integrations and JavaScript in-flight processing.
In choosing your event gateway tooling you should consider:
- The ease of working with both in development and ongoing operations.
- If it can integrate easily with the sources and destinations that you need.
- How much control it offers and whether it can process events in-flight
- The tooling it gives you to stay on top of monitoring.
- What happens when something goes wrong.
For a deeper review of the options available, see our in-depth comparison of five of the most popular event gateway tools.
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