Java CSV Libraries

uniVocity-parsers is a suite of extremely fast and reliable parsers for Java. It provides a consistent interface for handling different file formats, and a solid framework for the development of new parsers.

Jackson is a Java data binding framework and multi-format data serializer used to translate data structures into native language objects. It functions as a JSON data binding library and a streaming parser that reads and writes data as discrete tokens to process large datasets with minimal memory. The project distinguishes itself through a bytecode serialization accelerator that replaces standard reflection with generated bytecode to increase data binding speed. It employs a module-based extensibility model to support a wide range of formats beyond JSON, including XML, YAML, CSV, TOML, and bin

Spring Framework is an enterprise Java framework providing a comprehensive infrastructure for building server-side applications. It functions as a dependency injection container and a Java application framework designed to support scalable backend development through modular architecture. The project provides tools for aspect-oriented programming to intercept method calls using dynamic proxies, allowing the application of cross-cutting concerns such as security and transactions. It also includes a centralized system for managing object lifecycles and coordinating component wiring by injecting

Toon is a data serialization library and toolkit designed to convert complex objects into compact, human-readable formats optimized for large language models. By focusing on token efficiency, the library minimizes the context window footprint of structured data through techniques like key folding and tabular layout optimization. It provides a streaming-capable processor that handles the encoding and decoding of hierarchical data while maintaining structural integrity. The project distinguishes itself through its path-aware transformation pipeline and configurable serialization logic, which al

Polars is a high-performance columnar data processing library designed for efficient analytical workflows. It functions as a structured data library that organizes information into typed columns, utilizing the Apache Arrow memory format to enable zero-copy data sharing and cache-friendly, vectorized operations. The engine is built to handle large-scale tabular datasets, providing both local and distributed analytical runtimes that scale from single-machine environments to multi-node clusters. The project distinguishes itself through a sophisticated lazy query engine that constructs abstract e