Apache Arrow

Apache Arrow is a language-independent columnar memory format for flat and hierarchical data, engineered so that analytical systems can share data without copying or serializing it between processes. Instead of every tool inventing its own in-memory layout, Arrow defines one that CPUs and GPUs can process efficiently, and that dozens of languages and engines can read directly. It also ships Arrow Flight, an RPC framework for moving large Arrow datasets over the network at high throughput.

• Columnar in-memory format - Data is laid out by column, which suits vectorized, analytics-heavy workloads far better than row-oriented layouts.
• Zero-copy interchange - Systems hand each other the same memory buffers, eliminating the serialize/deserialize tax that dominates data movement.
• Arrow Flight - A gRPC-based transport purpose-built for streaming Arrow record batches between services.
• Broad language support - Official libraries span C++, Java, Python, Rust, Go, and more, so a shared format really is shared.

For APIs, Arrow matters most where data-heavy services need to move analytical payloads without the overhead that JSON or CSV impose. Arrow Flight is increasingly the answer for high-volume data APIs — market data, machine learning feature stores, and warehouse-to-warehouse pipes — where a conventional REST-over-JSON surface would collapse under the payload size. As agents and analytical tools consume ever-larger result sets, a provider offering an Arrow or Flight interface signals a data platform built for scale rather than convenience.