Confluent Announces Infinite Retention for Apache Kafka in Confluent Cloud

The original creators of Apache Kafka launch the only fully managed event streaming service to provide unlimited storage of real-time and historic events

Confluent, Inc., the event streaming pioneer, announced the next stage of its Project Metamorphosis initiative, which aims to build the next- generation event streaming platform any organization can put at the heart of their business. As part of the Infinite release, Confluent announces infinite retention, a new capability in Confluent Cloud that creates a centralized platform for all current and historic event streams with limitless storage and retention. Organizations can now democratize access to event data and ensure all events are stored and accessible as long as needed. By combining all relevant past and current event data, organizations can build richer application experiences and make more informed data-driven decisions.

“Without the context of historical data, it’s difficult to take action on real-time events in an accurate, meaningful way,” said Jay Kreps, co-founder and CEO, Confluent. “We’ve removed the limitations of storing and retaining events in Apache Kafka with infinite retention in Confluent Cloud. With event streaming as a business’s central nervous system, applications can pull from an unlimited source of past and present data to quickly become smarter, faster, and more precise.”

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Contextually rich, personalized applications are in especially high demand as digital experiences have replaced in-person interactions during the pandemic. In order to build these sophisticated touch points, applications need input data on what is happening right now and how that relates to what happened in the past. This is incredibly challenging and prohibitively costly for existing data architectures, especially when new events move through organizations at gigabyte-per-second scale. And due to high storage costs and complexities in data balancing, events are typically retained in Apache Kafka® for only seven days. This limits event streaming use cases, like year-over-year analysis and predictive machine learning, and is not often a long enough time for compliance reasons.

“Although Apache Kafka is widely used for event streaming, many limitations still exist because of high infrastructure costs associated with storing data for longer periods of time,” said Dave Menninger, SVP and Research Director, Ventana Research. “Being able to extend from days or weeks of retention to several years with less operational overhead, greatly increases the value event streaming brings to any organization.”

Introducing the Only Fully Managed Event Streaming Service with Unlimited Storage and Infinite Retention

With the new infinite retention capability in Confluent Cloud, Confluent solves the technical and economic strains put on organizations by the rapidly growing volume of real-time event streams. Organizations can now quickly and cost-effectively establish a central source of truth for all events across their entire ecosystem, unlocking more use cases for pervasive event streaming and mitigating the rising cost of Kafka storage.

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Implement Event Streaming as the Central Nervous System for All Real-Time Data

In traditional data architectures, silos exist between storage systems that record past data and messaging services that process future events. On top of that, there are hundreds of in-house systems, SaaS applications, and microservices linked together by point-to-point connections that create huge operational burdens. With infinite retention in Confluent Cloud, organizations can easily build one central nervous system where all events flow through and can be stored. Event streaming can become a single source of truth for all other systems, making it easy to scale and ensure data integrity across an entire business.

Do More with Streaming Applications

Within Kafka, compute and storage are tightly interlocked making it difficult to retain high volumes of data while efficiently scaling storage as traffic grows. Infinite retention decouples compute and storage and also automates scaling so storage instantly grows based on traffic. Without storage limitations, organizations are able to leverage event streaming for more use cases like providing a persistent log of all events for compliance audits that require several years of data. Infinite retention also makes it possible to train machine learning models to make real-time predictions based on a historical stream of data. With more data to draw from, infinite retention can also improve the accuracy and intelligence of existing event streaming use cases like recommendation engines and customer 360 analytics.

Reduce Storage Costs and B****** Complexities