ClickHouse vs Hadoop for Real-time Analytics

Introduction This article highlights why Hadoop may not be the best fit for real-time analytics and discusses how ClickHouse emerges as a more suitable solution. 10 Reasons Why Hadoop is Not Recommended for Real-Time Analytics: […]

ClickHouse vs Cassandra for Real-time Analytics

Introduction ClickHouse and Cassandra are both powerful data management systems, but they are designed for different use cases. 1. Data Model 2. Query Language 3. Aggregation 4. Data Compression 5. Indices 6. Throughput Conclusion The […]

ClickHouse Resource Safety: Implementing RAII and Destructors

Introduction In ClickHouse’s C++ codebase, efficient resource management and preventing resource leaks are crucial for ensuring stable and high-performance data processing. C++ provides the powerful RAII (Resource Acquisition Is Initialization) idiom, which allows resources to […]

ClickHouse Row Number Functions for High Performance

Introduction Row numbering methods play a crucial role in ClickHouse’s performance, particularly when dealing with extensive datasets and intricate queries. Different approaches, such as using the ROW_NUMBER() function, ARRAY JOIN clause, WITH ORDINALITY syntax, or […]

ChistaDATA’s ClickHouse v/s Hadoop for Real-time Analytics

Complexities in Cloudera Hadoop Infrastructure Operations Management: Why is Hadoop not scalable in modern real-time analytics? Why do corporations globally engage ChistaDATA for real-time analytics on ClickHouse? Conclusion By engaging ChistaDATA for real-time analytics on […]

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