Case Study: Iterable scales customer engagement and cuts costs with StreamNative's Apache Pulsar

How Apache Pulsar is Helping Iterable Scale its Customer Engagement Platform

Iterable, a MarTech company with 501–1000 employees, needed a more scalable and reliable messaging platform as its customer engagement system grew. Its RabbitMQ queues were showing flow-control issues, difficulty handling more than 10,000 queues, limited debugging visibility, and weak replication, while Kafka did not fit the company’s queueing needs. Iterable evaluated StreamNative’s Apache Pulsar as a way to support both streaming and work-queue workloads across message sends and other internal messaging use cases.

Using StreamNative’s Apache Pulsar, Iterable migrated its marketing message sends from RabbitMQ to Pulsar over about six months, first running parallel tests and then moving customers gradually with feature flags. Iterable also used Pulsar’s delayed messages, negative acknowledgements, shared subscriptions, and large-topic scalability, while contributing tooling such as pulsar4s support and an Akka Streams connector. The result was a smoother production rollout, a Pulsar cluster that has run for more than six months without issues, and nearly a 50% reduction in operational costs.

Iterable