
Explore the six key components of a Data Streaming Platform, from Apache Kafka to Tableflow, and learn how they work together to provide a complete solution for unified end-to-end data streaming across your organization.

Rethink data circulation using DataStreams and Change Data Capture. Learn to shift data preparation to creation point, building fresh datasets as streams for operational use or Apache Iceberg tables for analytics.

Explore real-time threat detection using machine learning, Apache Kafka, and ksqlDB. Learn about ZIEM, a network mapping and intrusion detection platform that generates instant network diagrams for quick anomaly detection.

Explore Striim's unified data streaming platform for rapid deployment of event stream pipelines, enabling real-time analytics and AI with built-in CDC and exactly-once processing.

Master data-in-motion techniques to accelerate trusted AI implementation, enhancing real-time data streaming across organizations for improved customer experiences and backend operations.

Explore Apache Kafka's next-generation rebalance protocol, enhancing stability and scalability for consumer groups in data streaming architectures.

Discover how serverless Flink revolutionizes real-time data processing, offering improved scalability, reduced costs, and increased flexibility. Learn to build low-latency applications focusing on business logic rather than infrastructure management.

Explore custom queries with Kafka Streams Interactive Queries v2. Learn to build IQ services, create tailored queries, and test applications for efficient state store access and business-aligned data processing.

Unlock real-time event streams to detect trends, issues, and threats. Learn how IBM Event Automation empowers teams to process events, define scenarios, and automate decisions.

Leverage Confluent Cloud on Azure to build real-time data flows, capture changes instantly, and simplify data pipeline development. Boost productivity and innovate faster with streaming data pipelines and self-service access.

Explore Shopify's Kafka infrastructure and learn how DNS traffic management and client wrappers enhance resilience, ensuring message production during incidents and maintenance.

Explore a unified architecture for stream processing, combining fast data storage to enhance simplicity, performance, and cost-efficiency in real-time data platforms.

Explore event-driven architecture for managing long-term customer data, addressing data quality issues, and evolving critical data structures in Social Security Administration systems.

Explore WarpStream's solution for Apache Kafka challenges, leveraging S3 for efficient streaming storage. Learn cost-saving strategies and witness live performance tests handling high-volume data ingestion.

Explore self-service environments using declarative APIs, focusing on creation, maintenance, and one-click consumption from development to production using kcp and Backstage.

Explore fundamental Apache Kafka concepts, including event-driven architecture, topics, producers, consumers, and key configurations. Gain confidence in learning this powerful platform.

Explore new features in Strimzi 0.32.0, including Kubernetes support, Control Plane Listener, Rebalance Auto-Approvals, OpenTelemetry, and cluster-ip type listener. Learn about upgrades and Apache Kafka versions.

Explore real-time personalization architecture using Apache Kafka and Spark for advanced content recommendation systems in data engineering and AI.

Explore Charmed Spark and Kafka: Canonical's solutions for Apache Spark and Kafka on Kubernetes. Discover industry trends, real-time applications, and data processing innovations.

Learn to build a houseplant monitoring system using Raspberry Pi, Apache Kafka, and ksqlDB. Create real-time alerts and gain hands-on experience with event-driven pipelines and stream processing.

Explore how Apache Kafka and Kafka Connect can streamline data pipelines, replacing complex ETL flows with efficient database change tracking and real-time data streaming for improved performance.