We live in a world in motion. Stream processing allows us to record events in the real world so that we can take action or make predictions that will drive better business outcomes. The real world is ...

Stream processing unifies applications and analytics by processing data as it arrives, in real-time, and detects conditions within a short period of time from when data is received. The key strength ...

On Confluent Cloud for Apache Flink®, snapshot queries combine batch and stream processing to enable AI apps and agents to act on past and present data New private networking and security features ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Cory Benfield discusses the evolution of ...

In one of its most significant product updates since going public, Confluent Inc. today introduced a new cloud-based toolkit to help enterprises analyze real-time data from their systems more ...

First commercial deployment of APU in European cloud addresses surging AI demand, enabling EU enterprises to accelerate Apache Spark workloads while maintaining full control over data TEL AVIV, Israel ...

Overview: Modern organizations rely on integrated data platforms to process massive datasets and generate real-time insights.Cloud-native platforms like Snowfla ...

Tapping edge computing and IoT devices for real-time analytics holds great promise, but designing analytical models for edge deployment presents a challenge. Many analytics and machine learning use ...