Confluent, founded by the creators of Apache Kafka, today announced the general availability of open source Confluent Platform 3.0. The new release introduces Kafka Streams, a powerful, lightweight solution to real-time processing designed to power a generation of highly responsive applications. With Kafka Streams, developers can quickly build core streaming applications such as fraud and security monitoring, Internet of Things (IoT) operations and machine monitoring, with concise code that is distributed and reliable.
Confluent Platform 3.0 also features Confluent’s first commercial product, the Confluent Control Center, that operationalizes Kafka across an organization, also announced today. To learn more, please visit:
Businesses are just beginning to recognize the sea change that real time data is bringing to organizational performance. With the proliferation of mobile devices and applications, a growing volume of Web application data, and the emergence of IoT as a competitive differentiator, data is increasingly taking the form of real-time streams. The faster companies respond to data, the better they can personalize services and offerings based on real-time customer engagement, react to shifting market dynamics and accelerate their business operations to outperform the competition.
“Data has a shelf life of value, and today’s consumers and business users demand immediate, highly personalized, responsive information,” said Neha Narkhede, cofounder and CTO of Confluent, and one of the creators of Kafka. “Stream data is becoming an organization’s customer interface backbone, fostering true customer intimacy that enables differentiation from competitors. Based on our Kafka expertise we’ve created a powerful, lightweight approach to stream processing.”
Introducing Kafka Steams — What Developers Need to Know
A simple solution to real-time processing, Kafka Streams is a stream processing layer that provides a new, native streaming development environment for Kafka. Developers will be able to leverage an easy-to-use library for building distributed stream processing apps using Kafka.
Kafka Streams is:
- Powerful — Supports stateful and stateless processing; distributed processing and fault tolerant; no downtime rolling deployments
- Lightweight — No dedicated cluster required; no message translation layer; no external dependencies
- Real-Time — Allows for late arrival of data; processes one event at a time; doesn’t microbatch messages like other stream processing solutions; windowing with out-of-order data
Industry Support for Apache Kafka and Confluent
“Businesses want to organize large amounts of live data to inform smart, timely business decisions, but often complexity is holding them back,” said Nik Rouda, senior analyst at ESG. “With Kafka Streams, Confluent is simplifying data streaming into a well-managed, unified data platform.”