As more data-intensive applications emerge, higher-performance, scalable, and domain-specific databases have become increasingly needed. In this paper, comparative benchmarking of three leading NoSQL databases, Redis, AstraDB, and Neo4j, each offering key-value, document/wide-column, and graph data models, respectively, is presented. The benchmarks contrast the performance of each database in performing basic CRUD operations by measuring execution time, CPU and memory consumption, disk I/O, and network throughput. In the experiment, a Python-based test framework is used that captures real-time system statistics based on the psutil library. The experiments reveal considerable performance trade-offs between the databases, with Redis being the most performance-focused and requiring the least memory, AstraDB offering document flexibility, and Neo4j offering superior performance in performing complicated relationship queries. This research facilitates informed database choice based on application-specific needs.