Apache Kafka
No written verdict yet. Here is what commenters said.
Why people recommend it
“I use Kafka as the example.”
“I don't know the internals of Kafka, RabbitMQ, or PostgreSQL. I just know how to use them. And yet they work fine.”
Show 3 more
“For multiple nodes, I use something like Kafka, where you write down one event, and have two systems subscribe to it”
“Because you can throw lava at it and it will eat it.”
“We built TBMQ on Kafka because it's battle-tested at scale across the industry”
Caveats and dissent
“I built QueueForge after repeatedly dealing with failed messages in RabbitMQ and Kafka.”
“Where Kafka starts to fall short is routing.”
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“I'm looking at you Kafka!”
“I owned Kafka and RabbitMQ clusters. Zero consideration was given to message size recommendations”
Often compared with
Amazon Web ServicesWho recommends it in their own words
From the makers not counted in the ranking
“I'm the author. This is a new feature design that was just accepted by the community”
Threads where it came up
- Ask HN: Who wants to be hired? (July 2026) 6 mentions
- Ask HN: Who wants to be hired? (October 2026) 5 mentions
- Ask HN: Who wants to be hired? (June 2026) 4 mentions
- Ask HN: Who wants to be hired? (February 2026) 4 mentions
- Small Kafka: Tansu and SQLite on a free t3.micro 4 mentions
- Ask HN: Who wants to be hired? (May 2026) 3 mentions
Also written as Apache Kafka. Data: apache-kafka.json. Quotes are verbatim; the verdict and theme labels are written by a model from these comments, and every clause links to its sources.
All comments 40
“I use Kafka as the example.”
“replaced a 20-30 person auction-scheduling team with an event-driven system on Celery and Kafka.”
“Kafka”
“PostgreSQL, Kafka, Redis”
“FastMCP, Kafka, Docker”
“redesigned it on top of kafka”
“using Redpanda/Kafka on Azure+Terraform”
“I built QueueForge after repeatedly dealing with failed messages in RabbitMQ and Kafka.”
“using Redpanda/Kafka on Azure+Terraform”
“Where Kafka starts to fall short is routing.”
“RabbitMQ/Kafka”
“6M+ telemetry messages/day through Kafka at 99.9% data integrity”
“I don't know the internals of Kafka, RabbitMQ, or PostgreSQL. I just know how to use them. And yet they work fine.”
“built the Kafka-based CDC streaming architecture”
“If I am at the scale where I really want Kafka, it is probably for performance and I just can't believe there's anyway Postgres could provide that.”
“For multiple nodes, I use something like Kafka, where you write down one event, and have two systems subscribe to it”
“For kafka connector we had a design partner”
“I'm looking at you Kafka!”
“Kafka”
“Kafka-backed observability pipelines processing 12M+ events/day”
“Apache Kafka”
“Technologies:”
“Kafka”
“built a Kafka-based event pipeline”
“microservices price tracker with Kafka and gRPC”
“Redis, Apache Kafka”
“Bash, Kafka, Redpanda”
“Java/Rust low-latency services with Kafka/Cassandra”
“The whole stack is open source, Kubernetes, Docker, Hashicorp tools, Postgres, Redis, MongoDB, RabbitMQ, NATS, Kafka, Prometheus, Elastic Search, Kibana, Grafana”
“event-driven systems (Kafka, SQS)”
“RabbitMQ/Kafka”
“Kafka still wins for very large data pipelines”
“Redpanda/Kafka on Azure+Terraform”
“Scale Kafka/NiFi ingestion pipelines”
“alongside AWS, Kafka, and Postgres”
Hey HN, Most integration failures look like data problems. They’re not. In my experience, they’re almost always delivery problems. An event never arrives. Or it arrives twice. Or out of order. And everything looks fine until something breaks. I’ve seen this more than once in production systems integrating with external APIs. Typical setup is webhooks + some retry logic + logs. When something fails mid-flight, debuggi
“we wrote from services to a kafka queue first”
“Because you can throw lava at it and it will eat it.”
“Terraform, Kubernetes, Docker, Kafka, PostgreSQL, Redis”
“Developed a real-time data pipeline with Kafka + Neo4j”