Columnar Storage

Columnar storage, a data organization method storing data by column rather than row, is increasingly crucial for efficient data processing in machine learning. Current research focuses on optimizing columnar databases for machine learning workloads, including developing specialized storage systems that handle sparse features and large-scale data, and adapting algorithms like gradient boosting to operate directly on columnar data within database systems. This enhances performance and scalability for various applications, from recommendation systems to generative AI, by minimizing data movement and improving I/O efficiency. The resulting improvements in speed and resource utilization are significant for both training and inference phases of machine learning models.