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Kafka

The Apache Pulsar Advantage: Why Tencent Moved from Kafka - Multi-Tenancy, Geo-Replication, and Tiered Storage in Practice

The Apache Pulsar Advantage: Why Tencent Moved from Kafka - Multi-Tenancy, Geo-Replication, and Tiered Storage in Practice

1 Introduction: The Scale Ceiling and the Architectural Pivot Streaming platforms behave very differently once they move past “large” and enter true enterprise scale. At modest volumes, most archi

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Operational Dashboards at Milli-Scale: Materialized Views, Columnstore & Redis Read Models

Operational Dashboards at Milli-Scale: Materialized Views, Columnstore & Redis Read Models

1 The Latency Gap: Why Standard Queries Fail at Scale Operational dashboards succeed only if they stay fast. When a dispatcher refreshes a fleet view or a support agent checks live customer metric

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Building Uber's Dynamic Pricing Engine in .NET: Supply-Demand Algorithms, Geospatial Indexing, and Real-Time Market Simulation

Building Uber's Dynamic Pricing Engine in .NET: Supply-Demand Algorithms, Geospatial Indexing, and Real-Time Market Simulation

1 Building Uber’s Dynamic Pricing Engine in .NET: Supply-Demand Algorithms, Geospatial Indexing, and Real-Time Market Simulation Uber’s pricing engine is one of the most fascinating real-time syst

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ClickHouse vs. Cassandra vs. ScyllaDB: Choosing a High-Ingest Database for Real-Time Analytics

ClickHouse vs. Cassandra vs. ScyllaDB: Choosing a High-Ingest Database for Real-Time Analytics

1 Why high-ingest real-time analytics is hard (and worth it) In today’s world of digital services, sensors, user interactions, and complex systems, the demand isn’t just for storing massive volume

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Change Data You Can Trust: An Architect's Guide to CDC, Auditing, and CQRS in .NET

Change Data You Can Trust: An Architect's Guide to CDC, Auditing, and CQRS in .NET

1 The Inevitability of Change: Why Capturing Data Evolution is Mission-Critical Every system we design in .NET eventually collides with the same truth: data does not stay still. Orders are created

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Beyond Queues: Architecting Real-Time Data Streaming and Analytics Pipelines in .NET with Kafka and Apache Flink

Beyond Queues: Architecting Real-Time Data Streaming and Analytics Pipelines in .NET with Kafka and Apache Flink

1 Introduction: The Evolution from Batch to Real-Time 1.1 The Limitations of Traditional Batch Processing For decades, businesses relied on nightly batch jobs to process transactional data. T

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