Messaging and Queuing for Data in Motion

Unified messaging and queuing designed for performance, durability and ease of use

Rapidly moving data between sources and applications is critical to handling streaming data. However, legacy technologies for messaging and streaming are cumbersome to use and burdensome to operate.

Streamlio provides best-in-class messaging and queuing powered by Apache Pulsar, the open source streaming messaging solution developed and hardened in production at Yahoo! to support demanding applications including Yahoo! Mail, Yahoo! Finance, Yahoo! Sports, Flickr, and the Gemini ads platform. Pulsar has been proven in production, delivering robust messaging with the simplicity, durability, and performance needed for data-driven applications that can scale to handle over 1 million topics and over 100 billion messages per day.

An introduction to the Apache Pulsar architecture


Pulsar is a messaging solution for streaming data that supports both publish-subscribe messaging, message queuing, and easy stream processing in a unified solution. Developed at Yahoo!, Pulsar has been proven in production, handling millions of topics and messages per second.

Unique architecture

A scale-out message processing layer combined with the Apache BookKeeper stream storage solution provide the combination of performance, durability, and scalability needed for modern streaming

Proven performance

Scale-out architecture, performance isolation of read and write operations, and fine-grained tunability provide low latency and high throughput for publishing and consuming data deliver leading performance

No data loss

Data persistence guarantees and built-in multi-datacenter replication across datacenters and geographic regions ensure that data is always protected and available without needing additional components or complex configurations

Easy scalability

Independent scaling of message processing and streaming data storage, without data redistribution, make it possible to scale on the fly to support millions of topics and messages per second


Designed with the security, isolation, resource management, and scalable performance needed to support large numbers of topics, publishers and consumers in a single solution to avoid the complexities of siloed data

Ease of use

Unified publish-subscribe and queuing in one solution, multi-language API, Kafka compatibility, and support for the OpenMessaging standards make it easy to develop data flows that meet the needs of diverse streaming applications