Confluent vs. Google Cloud Pub/Sub

If your company needs to build event-driven applications, like in healthcare industry, you need to enhance interoperability, and you are seeking a reliable service with enterprise-grade support, Confluent is the best on the market you can get. Their product works great and they provide very good customer service.

Incentivized

Using Google Cloud Pub/Sub will mainly depend on the cloud platform used. Our client didn't choose GCP for Google Cloud Pub/Sub, if we went with AWS we would be using SNS/SQS (obviously). However, Google Cloud Pub/Sub is a better solution in the GCP services compared to self-managed solutions such as RabbitMQ for instance (it is managed by GCP and integrates with GCP solutions).

Incentivized

• Products work great.
• Training is available.
• Customer support is good.

Incentivized

• A hands-off approach to publishing messages and subscribing to topics.
• Easy to use APIs.
• Useful, simple UI on cloud console to send messages for debugging, etc.

Incentivized

• Cloud based Azure platform features for Confluent lacks behind AWS And GCP

Incentivized

• It is limited to work with the same platform but with different datasets at the same time, you must request a prior security authentication.
• It can sometimes lead to unexpected charges, as Pub/Sub will automatically keep on retrying messages continuously, even if failures are due to permanent code-level issues.
• Message re-deliveries don't apply for ingested services like with Python based client. Push messages tried to be delivered immediately and if your service is busy dealing with some other task, it won't be done OR goes into a queue

Incentivized

It serves all of our purposes in the most transparent way I can imagine, after seeing other message queueing providers, I can only attest to its quality.

It has many libraries in many languages, google provides either good guides or they're AI generated code libraries that are easy to understand. It has very good observability too.

I have never faced a single problem in 4 years.

It's very fast, can be even better if you use protobuf.

The support from the Confluent platform is great and satisfying. We have been working with Confluent for more than a year now. They sent out resident architects to help us set up Confluent cluster on our cloud and help us troubleshoot problems we have encountered. Overall, it has been a great experience working with the Confluent Platform.

Incentivized

They have decent documentation, but you need to pay for support. We weren't able to answer all our questions with the documentation and didn't have time to setup support before we needed it so I can't give it a higher rating but I think it tends to be a bit slow unless you're a GCP enterprise support customer.

Incentivized

For our use case it was very important that the technology we were working with fit into our Azure architecture, and met our data processing size requirements to stream data within certain SLAs. Confluent more than met our performance requirements and compared to the others scale options and cost to run it was more than financially viable as a platform solution to our global operations.

Incentivized

• Easy to setup Publisher, Subscribers and Message Queue service
• More Reliable and Easy Scalable with Google Managed services
• Easily integrated with most of the data sources we typically use for Data Storage and Analysis
• 10k Topics is a good enough number to build and deliver the business use cases
• Asynchronous and fallback mechanisms are great to ensure parallel delivery of the messages

Incentivized

You can just plug in consumers at will and it will respond, there's no need for further configuration or introducing new concepts. You have a queue, if it's slow, you plug in more consumers to process more messages: simple as that.

• Confluent replaced Microsoft Event Hubs in our environment and unblocked data platform services rollout globally.

Incentivized

• Pub/Sub has helped avoid data loss improving our customer value prop.
• Pub/Sub has reduced development time that would otherwise be needed to build a highly scalable queue.

Incentivized