Apache Parquet has long been the standard for analytical data storage, but modern workloads, particularly in AI and machine learning, highlight its limitations in random access and performance. As a result, new file formats like BtrBlocks, FastLanes, Lance, and Nimble are emerging, each designed to optimize for specific use cases and hardware architectures, offering faster decompression and improved efficiency. These innovations reflect a shift towards more dynamic data access needs that Parquet was not originally built to address.