GPU Database refers to a class of database systems and data processing architectures that leverage the massive parallel processing power of graphics processing units to store, manage, and analyze large volumes of data at very high speeds. Unlike traditional databases that rely primarily on central processing units, GPU databases are designed to offload compute-intensive operations such as filtering, aggregation, sorting,
joins, and machine learning workloads to GPUs, which excel at handling thousands of operations simultaneously. This approach significantly accelerates data processing, making GPU databases particularly suitable for real-time analytics, big data workloads, and high-performance computing scenarios. The core concept behind a GPU database is parallelism, as GPUs contain thousands of small cores optimized for executing the same operation across large datasets.
By organizing data in memory-friendly formats and minimizing data movement between CPU and GPU, these systems achieve dramatic improvements in query performance and throughput. GPU databases often store data…