Apache Arrow
Apache Arrow is a cross-language development platform for in-memory analytics developed by the Apache Software Foundation. It specifies a standardized, language-independent columnar memory format for flat and nested data, organized for efficient analytic operations on modern hardware including CPUs and GPUs. Arrow provides computational libraries in C++, Java, Python (PyArrow), R, Go, Rust, JavaScript, C#, Ruby, Julia, and Swift, along with zero-copy streaming messaging via IPC and a high-performance data transfer framework called Arrow Flight (built on gRPC).
Apache Arrow publishes 3 APIs on the APIs.io network. Tagged areas include Analytics, Apache, Columnar Format, Data, and gRPC.
Apache Arrow’s developer surface includes documentation, getting-started guide, support, changelog, engineering blog, and 15 more developer resources.
Kin Score
APIs 3
Individual APIs this provider publishes, each with its own machine-readable definition.
Apache Arrow Flight RPC
Arrow Flight is a high-performance RPC framework built on gRPC for transferring large datasets using the Arrow columnar format. It enables efficient bulk data transport between ...
Apache Arrow Libraries
Arrow provides native libraries in C++, Java, Python (PyArrow), R, Go, Rust, JavaScript, C#, Ruby, Julia, and Swift for reading, writing, and processing columnar data in the Arr...
Apache Arrow Format Specification
The Apache Arrow columnar format specification defines the binary layout for in-memory columnar data, including the IPC format for streaming and file-based data exchange. It cov...
Pricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Apache Arrow Rate Limits
RATE LIMITSFinOps 1
Cost, billing, and metering signals for API financial operations.
Apache Arrow Finops
FINOPSFeatures 10
Notable capabilities this provider offers.
Columnar In-Memory Format
Standardized language-independent columnar memory layout for efficient analytic operations with zero-copy access.
Arrow Flight RPC
High-performance gRPC-based framework for transferring large Arrow datasets between services with minimal serialization overhead.
Flight SQL
Extension of Arrow Flight providing a SQL query execution interface over the Arrow Flight protocol.
Zero-Copy IPC
Inter-process communication via shared memory and memory-mapped files, enabling zero-copy data sharing across process boundaries.
Multi-Language Support
Native libraries for C++, Java, Python, R, Go, Rust, JavaScript, C#, Ruby, Julia, and Swift.
Vectorized Computation
SIMD-optimized compute functions for analytical operations on Arrow arrays and tables.
Parquet Integration
First-class support for reading and writing Apache Parquet files via the Arrow columnar format.
Dataset API
Unified Dataset API for reading partitioned datasets from local filesystems, S3, GCS, and HDFS.
GPU Support
CUDA integration for zero-copy data sharing between CPU and GPU memory via the CUDA Arrow device.
Extension Types
Custom extension types for encoding domain-specific data using the Arrow format.
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Security Posture 2
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Use Cases 6
What developers build with this provider.
Analytics Data Exchange
Share large analytical datasets between Python, R, Java, and other runtimes without serialization overhead.
Database Query Results
Return query results from databases in Arrow format for fast analytics without Python/Java deserialization.
Data Pipeline Acceleration
Accelerate ETL and data processing pipelines using columnar computation and SIMD optimizations.
Machine Learning Feature Stores
Store and serve ML features in Arrow format for efficient batch and real-time feature retrieval.
High-Throughput Data Services
Build high-throughput data microservices using Arrow Flight for efficient bulk data transfer over gRPC.
Cross-Language Data Sharing
Share in-memory data between Python pandas/polars, Java, and Rust applications with zero-copy semantics.
Integrations 8
Pre-built integrations with other platforms and tools.
Apache Parquet
Native read/write support for Parquet columnar file format, the most common big data storage format.
Apache Spark
Spark uses Arrow for Python UDF execution and pandas-on-Spark operations via PyArrow.
pandas
Deep integration with pandas DataFrames via PyArrow's to_pandas() and from_pandas() conversions.
DuckDB
DuckDB uses Arrow as its primary in-memory data format for zero-copy query result exchange.
Polars
Polars DataFrame library is built on Arrow and supports zero-copy interop with Arrow arrays.
ADBC (Arrow Database Connectivity)
Arrow Database Connectivity provides an Arrow-native database driver interface analogous to ODBC/JDBC.
Delta Lake
Delta Lake integrates with Arrow for reading and writing Delta table data in columnar format.
Ray
Ray distributed computing framework uses Arrow for shared-memory object storage between workers.
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Resources
Get Started 1
Portal, sign-up, and the first successful call
Documentation 1
Reference material describing how the API behaves
Build 11
SDKs, sample code, and the tooling you integrate with
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Access & Security 2
Authentication, authorization, and security posture
Operate 2
Status, limits, changes, and where to get help
Commercial 1
Pricing, plans, and the legal terms of use
Company 2
The organization behind the API