Apache Arrow is 10 years old
Apache Arrow, the ubiquitous columnar data format, celebrates its tenth anniversary, reflecting on a decade of stable standards and widespread adoption. The project highlights its initial goals, remarkable format stability (with only one breaking change), and the vast ecosystem it has fostered. Its popularity on HN stems from its foundational role in data engineering and analytics, touching nearly every modern data stack.
The Lowdown
The Apache Arrow project marks its 10-year anniversary, looking back at a decade of growth and impact as a cornerstone for efficient data exchange. Established on February 5th, 2016, Arrow set out to provide agnostic, efficient, and durable standards for columnar data, a goal it has demonstrably achieved.
- Arrow originated from a joint effort to create common ground for exchanging columnar data, serving as an in-memory complement to Apache Parquet's persistent storage format.
- Its initial 0.1.0 release in October 2016 already featured core data types, with the foundational columnar format remaining remarkably stable, experiencing only one minor breaking change related to Union types.
- The IPC (Interprocess Communication) format has evolved with versioning to ensure backward compatibility, mitigating issues from metadata changes.
- Cross-language integration tests were introduced in late 2016, becoming crucial for ensuring consistency across multiple implementations and preserving backward compatibility.
- The project reached version 1.0.0 in July 2020, signaling its maturity and formal commitment to compatibility for a broad data ecosystem.
- Today, Arrow's influence spans numerous specifications (like zero-copy sharing and ADBC), official implementations in languages such as C++, Java, Python, and Rust, and a thriving ecosystem of subprojects (e.g., ADBC, nanoarrow, Apache DataFusion) and third-party adoptions (e.g., GeoArrow).
- Arrow's strong synergy with Parquet continues, with Arrow repositories now hosting most official Parquet implementations.
- The project continues to be community-driven, focusing on maintenance, performance improvements, and welcoming contributions to its ever-expanding ecosystem.
Arrow's journey over the past decade exemplifies the power of open-source collaboration in establishing a critical standard that underpins much of modern data processing, promising continued innovation and stability for the future.