- casestudy
- llm
- genai
- quantum-computing
- code
- platform
- algorithms
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The Next Frontier - Envisioning the Future of Data Platforms Beyond Data Mesh, Data Lakehouse, and Data Hub/Fabric
Advancements in data management, from warehouses to Data Mesh and Lakehouse, signal a shift toward more adaptive platforms like, Quantum Data Management, Genetic algorithm concepts, etc.
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Part 4 - Building a Massive-Scale Real-Time Data Platform - Memory Management with Apache Ignite
Deep dive into memory management with Apache Ignite for high-performance data platforms. Learn how to handle 2.5M events/second with sub-millisecond latency through practical memory architecture, optimization techniques, and real-world implementation patterns.
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Part 3 - Building a Massive-Scale Real-Time Data Platform - Memory Management with Apache Ignite
Deep dive into memory management with Apache Ignite for high-performance data platforms. Learn how to handle 2.5M events/second with sub-millisecond latency through practical memory architecture, optimization techniques, and real-world implementation patterns.
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Part 2 - Building a Massive-Scale Real-Time Data Platform - Data Partitioning and Flow
Explore how to architect data partitioning and flow for massive-scale event processing. Learn implementation patterns for handling 2.5M events/second across distributed systems using Kafka, Ignite, and Cassandra. Practical insights on partition strategies, data routing, and performance optimization.
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Part 1 - Building a Massive-Scale Real-Time Data Platform - System Overview and Architecture
Dive into the architecture of a telco-scale real-time data platform processing 2.5M events/second and 350GB DPI data/15min. Learn how we combined Apache Kafka, Ignite, and Cassandra to build a high-performance system handling massive telecommunications data for real-time analytics and customer insights.