This book compiles eight groundbreaking research schemes that are shaping the future of big memory systems--massive-scale architectures where terabytes of persistent, byte-addressable memory eliminate traditional storage bottlenecks by unifying memory and storage hierarchies. For engineers and architects building next-generation databases and distributed systems, these innovations deliver transformative performance: faster persistent writes through optimized flush mechanisms, the reduced contention via lock-free designs, and unprecedented throughput using GPU acceleration. Each chapter presents fully realized architectures tested in real-world environments, from learned indexes to RDMA-powered transactions, complete with deployable code patterns and performance benchmarks. This book shows new devices are leveraging big memory to achieve microsecond-latency persistence, hardware-accelerated data processing, and linear scalability in distributed environments. Designed for professionals with operating systems fundamentals, this book bridges cutting-edge research with practical implementation--where big memory's unique characteristics (persistence at DRAM speeds, massive capacity, and fine-grained access) demand fundamentally new architectural approaches. Learn how to achieve faster queries with memory-disaggregated learned indexes, how to optimize cuckoo hashing for persistent memory's asymmetric costs, and why the latest GPUs incorporate these persistence techniques. This book also provides efficient and useful toolkit: the RDMA protocols have been adopted in storage tiers, while the lock-free designs power real-time recommendation systems. Whether building cloud-native databases, low-latency recommendation systems, or memory-driven AI services, these solutions will help harness the full potential of the big memory.