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https://star-history.com/#Apache/kafka&Apache/pulsar&Timeline It’s even more visible on aligned timeline

the marketing budget?

the challenge is that the kafka protocol sort of become a standard, additionally you have hosted service provided by aws, so that gives the platform free large scale marketing

The Kafka trend is constant, Pulsar trends is slowing

I do think a large part is the lack of awareness around Pulsar. By now, almost any company has heard of Kafka before but when talking to people I often see that they have not heard of Pulsar before. In order to change that we need to do 2 things 1) lower the barrier for new users and contributors as much as possible (descriptive, easy-to-use website that is up to date with relevant content) 2) raise awareness for Pulsar through conferences/talks/podcasts/blogs etc

I agree Pulsar definitely needs more awareness. About the website: a pull request is coming 🙂 Regarding the conferences, podcasts, and blogs: StreamNative is creating content but more content is needed from the community. I would be more than happy to support anyone planning to create content. Feel free to reach out 🙂

I submitted a similar question on Reddit’s /r/dataengineering an hour ago. https://www.reddit.com/r/dataengineering/comments/19dry3i/what_do_you_think_about_apache_pulsar/ For now, it has two answers. • Does Pulsar supports exactly-once message delivery? • 9+ instances for a minimal setup is too much for most projects. I hope there will be more. If you have anything to add, do it. And Upvote it! :)

Another contributing factor to the slowdown in Pulsar is that one of the 2 major companies promoting Pulsar has pivoted to the AI space with LangStream from a marketing perspective.

Maybe Pulsar also should add more AI-related content to its marketing? For a while until this hype calms down.

That’s sort of what LangStream is. RAG generation using Pulsar functions to feed your LLMs

Then LangStream should add more Pulsar in its marketing. 🤣 I see many logos on its home page, but can’t find any Pulsar mention, except for in technical docs pages like “Configuration for a LangStream streaming instance.”

My understanding is that the use of Pulsar functions is an internal (hidden) detail.

Our stack is Pulsar + SmallRye reactive messaging + Quarkus. It’s super easy to integrate it with llm https://quarkus.io/blog/quarkus-meets-langchain4j/

I've been working with Apache Pulsar on AWS for a month and am prepping to write a series of articles as I found the documentation to be scattered at multiple places. I plan to cover topics like: 1. Pulsar Clusters on AWS: TLS, ELB, and persistent storage. 2. Producers & Consumers: Using Spring Boot and Python. 3. Deployment: Tips for AWS EKS. 4. Monitoring: Setting up Grafana dashboards in AWS too. 5. Subscription Models: Demo apps and guidance. • I'd value your input: are these topics helpful? • Also, if anyone's up for reviewing or contributing, that'd be fantastic! Open for suggestions too as someone who has just started what can I contribute at the moment. Cheers!

That's great, @Shivam Rastogi! Yes, these topics are definitely useful. Feel free to reach out to me, I can help

Regarding the tutorials and low-entry examples. SmallRye and Pulsar test container integrated with Quarkus is a no brainer. One dependency and you are ready to develop event-streaming apps in Java: https://github.com/quarkusio/quarkus-quickstarts/tree/main/pulsar-quickstart Both Quarkus and Pulsar are cloud-native, so it’s definitely a way to go.

> Both Quarkus and Pulsar are cloud-native, so it’s definitely a way to go. There's also Spring Pulsar, you can start creating your Pulsar applications directly at https://start.spring.io/ .

That’s a great contribution, which can bring a lot of new developers into the field. We’ve been evaluating Spring+Reactive clients in 2022, we made a decision to use Quarkus and SmallRye Reactive Messaging. I’ve became a big fan of SmallRye/Quarkus/GraalVM stack, especially in regard to microservices and K8S. The engineering behind (and IBM/RedHat support) makes the integration with Pulsar much more advanced, but has one disadvantage, it’s not Spring :)

The engineering behind (and IBM/RedHat support) makes the integration with Pulsar much more advanced, but has one disadvantage, it’s not Spring :)

What makes the Quarkus solution and reactive integration more advanced? I doubt that it is solving reactive non-blocking back pressure properly for publishing or has key-ordered processing support like pulsar-client-reactive does. There are multiple details that matter in real world reactive applications. The docs of pulsar-client-reactive is lacking full explanations of these details.

It has a great abstraction of channels, you can develop your application using in-memory connectors and switch it to Pulsar in containerized app. In most of the cases it works. You can switch the messaging systems, if you do not use dedicated Pulsar features like transactions in a microservice. You can work locally with Pulsar using test containers with live reloading and debugging using juse ‘quarkus dev’ It’s has full integration with metrics, otel, micro-profile config or health checks. The whole ecosystem is just designed for containers/k8s It has built in support for GraalVM build. It has clear API and programming model based on Mutiny ir Java Phblishers. You can leverage Vertex and its event loop. It has full coverage of Pulsar client config, which can be overridden by configs from env, properties or any other sources (like zookeeper) We’ve been trying both. My team loves Smallrye/Quarkus ecosystem.

Thanks for sharing @Michał Cukierman. It looks very impressive and well documented.