ZeroMQ

Vadim Shalts’s Story

“I am team leader in the company ActForex, which develops software for financial markets. Due to the nature of our domain, we need to process large volumes of prices quickly. In addition, it’s extremely critical to minimize latency in processing orders and prices. Achieving a high throughput is not enough. Everything must be handled in a soft real time with a predictable ultra-low latency per price. The system consists of multiple components exchanging messages. Each price can take a lot of processing stages, each of which increases total latency. As a consequence, low and predictable latency of messaging between components becomes a key factor of our architecture.

“We investigated different solutions to find one suitable for our needs. We tried different message brokers (RabbitMQ, ActiveMQ Apollo, Kafka), but failed to reach a low and predictable latency with any of them. In the end, we chose ØMQ used in conjunction with ZooKeeper for service discovery. Complex coordination with ØMQ requires a relatively large effort and a good understanding, as a result of the natural complexity of multithreading. We found that an external agent like ZooKeeper is a better choice for service discovery and coordination while ØMQ can be used primarily for simple messaging. ØMQ perfectly fit into our architecture. It allowed us to achieve the desired latency using minimal efforts. It saved us from a bottleneck in the processing of messages and made processing time very ...