Unified solution for streaming and real-time data

Proven, best-of-breed technology for messaging, queuing, real-time processing, and stream storage

The Streamlio Solution

Today’s data-driven applications need to respond and react to data immediately. Streamlio brings together proven, enterprise-grade technology for connecting and processing fast-moving data in real-time. Built on best-in-class open source technologies for messaging, processing, and stream storage, Streamlio connects data to power data-driven applications. Streamlio’s core technologies–Apache Pulsar* for messaging, Heron for processing, and Apache BookKeeper stream storage–have been proven in production at extreme scale by companies including Twitter and Yahoo.

Diagram of Streamlio real-time solution components

Streamlio offers

  • Best-of-breed messaging, queuing, processing, and stream storage
  • Enterprise-grade data durability and resiliency to ensure zero data loss
  • Compelling performance and scalability
  • Multi-datacenter replication
  • Blazingly fast stream processing at scale
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Webcast: Building Data-Driven Microservices

Join Dr. Karthik Ramasamy of Streamlio as he draws on his experience building data products at companies including Pivotal, Twitter, and Streamlio to discuss key concepts, technology and best practices for designing and implementing data-driven microservices.

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Use cases

The Streamlio unified solution is built on open source technologies that have been proven in production at Twitter and Yahoo, powering event-driven use cases. The types of use cases that can take advantage of a real-time solution are limitless, but here are a few to start with:

Event-driven architecture


Break apart monolithic applications to build a new generation of applications enabled by microservices. These services can be independently developed and maintained, paving the way to lower development and operations costs and faster time to market.

Anomaly detection


Use event-driven actions to detect unusual patterns in real time. These events can include:

  • fraud detection for the finance and the insurance industries
  • real-time alerting and prevention of catastrophic defects in machines for manufacturing
  • intrusion detection for point of sale systems in online retail

Predictive modeling


Machine learning in real time—with no humans in the loop—to build intelligent applications. Uses of machine learning include:

  • smart homes and cities to preserve scarce resources like water and electricity
  • self-driving vehicles reducing accidents and minimizing traffic
  • financial investing to maximize returns and minimize losses

© 2018 Streamlio, all rights reserved. Apache BookKeeper, Apache DistributedLog, Apache Pulsar (incubating) are trademarks of The Apache Software Foundation.

*Apache Pulsar is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by Apache Incubator PMC. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.