wtf is jackson-dataformat-spade?

Spade is an experimental data format that organizes information by columns rather than by rows. While most common data formats bundle all the fields of a single record together before moving on to the next, this project groups all the values from a single field together. The key benefit is speed: it is designed to let systems encode and decode data fast enough to use while data is actively moving through a system, rather than only when it is sitting still in long-term storage. Most existing column-oriented formats are built for massive storage files. This project takes a different approach by keeping its data chunks much smaller, in the kilobyte range rather than the tens of megabytes. This keeps the memory requirements low for the software doing the reading and writing, and it reduces the delay before a chunk of data can be processed. It also lets processing systems interact with the data as if it were standard rows or records, meaning the software does not need to be specially programmed to understand the underlying column structure. Another notable feature is that the format supports both text and binary versions. The binary version is for efficiency, but the text version exists to make troubleshooting easier and to work with platforms like JavaScript that struggle with raw binary data. Because the underlying structure is the same for both, systems can easily convert between them. Developers building data pipelines or streaming applications would use this when they need fast, lightweight data processing. For example, a team building a system to filter or transform data on the fly could use it to process information with lower latency and less memory overhead than traditional storage-focused formats require. The README notes that further technical details are available in the project's wiki.