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Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Modernize your data layer. Learn how to design cloud-native database architectures to meet the evolving demands of AI and GenAI workkloads.

Secure your stack and shape the future! Help dev teams across the globe navigate their software supply chain security challenges.

Releasing software shouldn't be stressful or risky. Learn how to leverage progressive delivery techniques to ensure safer deployments.

Avoid machine learning mistakes and boost model performance! Discover key ML patterns, anti-patterns, data strategies, and more.

Introducing Apache Druid

Apache Druid was invented to address the lack of a data store optimized for real-time analytics. Druid combines the best of real-time streaming analytics and multidimensional OLAP with the scale-out storage and computing principles of Hadoop to deliver ad hoc, search and time-based analytics against live data with sub-second end-to-end response times. Today, thousands of companies worldwide rely on Druid to provide real-time monitoring and analytics, including data-driven companies like Netflix, Lyft, Pinterest and Alibaba. The largest Druid deployments deliver sub-second analytics against millions of events per second and 100s of petabytes of data.

This whitepaper provides an introduction to Apache Druid, including its evolution, core architecture and features, and common use cases.

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