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Vikram Patel
Independent Researcher
India
Abstract
This manuscript evaluates the performance, scalability, consistency, and suitability of leading NoSQL databases for big data applications as of 2016. It compares key‐value, document, column‐family, and graph stores—including Apache Cassandra, MongoDB, HBase, and Neo4j—against traditional relational systems under workloads characteristic of large‐scale data analytics, real‐time stream processing, and semi‐structured data management. Using controlled benchmarks, case studies from telecommunications and e-commerce, and performance metrics collected on a 50-node Hadoop cluster, we demonstrate trade-offs between throughput, latency, fault tolerance, and consistency. Our findings guide engineers in selecting appropriate NoSQL stores based on workload profiles and highlight configuration best practices prevalent in 2015.
Keywords
Evaluation, NoSQL, Big Data, Cassandra, MongoDB, HBase, Scalability
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