Apache Arrow

aid: apache-arrow
name: Apache Arrow
description: 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).
type: Index
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
position: Consumer
access: 3rd-Party
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/apache-arrow.png
tags:
- Analytics
- Apache
- Columnar Format
- Data
- gRPC
- In-Memory
- IPC
- Open-Source
- Python
tags_raw:
- Analytics
- Apache
- Columnar Format
- Data
- gRPC
- In-Memory
- IPC
- Open Source
- Python
created: '2026-03-16'
modified: '2026-04-19'
url: https://raw.githubusercontent.com/api-evangelist/apache-arrow/refs/heads/main/apis.yml
specificationVersion: '0.23'
apis:
- aid: apache-arrow:apache-arrow-flight-rpc
  name: Apache Arrow Flight RPC
  description: 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 services with client libraries available in C++, Java,
    Python, R, Go, and Rust. Flight SQL extends Flight with a SQL-over-Arrow interface for database query execution.
  humanURL: https://arrow.apache.org/docs/format/Flight.html
  tags:
  - Data Transfer
  - gRPC
  - RPC
  properties:
  - type: Documentation
    url: https://arrow.apache.org/docs/format/Flight.html
  - type: APIReference
    url: https://arrow.apache.org/docs/format/FlightSql.html
- aid: apache-arrow:apache-arrow-libraries
  name: Apache Arrow Libraries
  description: 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 Arrow in-memory format. Libraries enable zero-copy data
    sharing between processes and language runtimes.
  humanURL: https://arrow.apache.org/docs/
  tags:
  - Data Processing
  - Libraries
  - SDK
  properties:
  - type: Documentation
    url: https://arrow.apache.org/docs/
  - type: APIReference
    url: https://arrow.apache.org/docs/python/api.html
- aid: apache-arrow:apache-arrow-format
  name: Apache Arrow Format Specification
  description: 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 covers flat arrays, nested structures, dictionaries, and
    extension types.
  humanURL: https://arrow.apache.org/docs/format/Columnar.html
  tags:
  - Format
  - IPC
  - Specification
  properties:
  - type: Documentation
    url: https://arrow.apache.org/docs/format/Columnar.html
  - type: Specification
    url: https://arrow.apache.org/docs/format/Versioning.html
common:
- type: IssueTracker
  url: https://github.com/apache/arrow/issues
- type: Releases
  url: https://github.com/apache/arrow/releases
- type: CodeOfConduct
  url: https://github.com/apache/arrow/blob/main/CODE_OF_CONDUCT.md
- type: ContributionGuide
  url: https://github.com/apache/arrow/blob/main/.github/CONTRIBUTING.md
- type: License
  name: Apache-2.0
  url: https://github.com/apache/arrow/blob/main/LICENSE
- type: VulnerabilityDisclosure
  url: security/apache-arrow-vulnerability-disclosure.yml
- type: DomainSecurity
  url: security/apache-arrow-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/apache-arrow
- type: GitHubOrganization
  url: https://github.com/apache
- type: GitHubRepository
  url: https://github.com/apache/arrow
- type: GitHubRepository
  url: https://github.com/apache/arrow-rs
- type: GitHubRepository
  url: https://github.com/apache/arrow-java
- type: GitHubRepository
  url: https://github.com/apache/arrow-go
- type: GitHubRepository
  url: https://github.com/apache/arrow-js
- type: Documentation
  url: https://arrow.apache.org/
- type: GettingStarted
  url: https://arrow.apache.org/docs/python/getstarted.html
- type: Support
  url: https://arrow.apache.org/community/
- type: TermsOfService
  url: https://www.apache.org/licenses/
- type: ChangeLog
  url: https://arrow.apache.org/blog/
- type: SDKs
  url: https://pypi.org/project/pyarrow/
  title: PyArrow (Python)
- type: SDKs
  url: https://search.maven.org/artifact/org.apache.arrow/arrow-vector
  title: Apache Arrow Java (Maven)
- type: SDKs
  url: https://crates.io/crates/arrow
  title: Arrow-rs (Rust, crates.io)
- type: SDKs
  url: https://pkg.go.dev/github.com/apache/arrow/go/v15
  title: Arrow Go
- type: SDKs
  url: https://www.npmjs.com/package/apache-arrow
  title: Apache Arrow JavaScript (npm)
- type: Features
  data:
  - name: Columnar In-Memory Format
    description: Standardized language-independent columnar memory layout for efficient analytic operations with zero-copy
      access.
  - name: Arrow Flight RPC
    description: High-performance gRPC-based framework for transferring large Arrow datasets between services with minimal
      serialization overhead.
  - name: Flight SQL
    description: Extension of Arrow Flight providing a SQL query execution interface over the Arrow Flight protocol.
  - name: Zero-Copy IPC
    description: Inter-process communication via shared memory and memory-mapped files, enabling zero-copy data sharing across
      process boundaries.
  - name: Multi-Language Support
    description: Native libraries for C++, Java, Python, R, Go, Rust, JavaScript, C#, Ruby, Julia, and Swift.
  - name: Vectorized Computation
    description: SIMD-optimized compute functions for analytical operations on Arrow arrays and tables.
  - name: Parquet Integration
    description: First-class support for reading and writing Apache Parquet files via the Arrow columnar format.
  - name: Dataset API
    description: Unified Dataset API for reading partitioned datasets from local filesystems, S3, GCS, and HDFS.
  - name: GPU Support
    description: CUDA integration for zero-copy data sharing between CPU and GPU memory via the CUDA Arrow device.
  - name: Extension Types
    description: Custom extension types for encoding domain-specific data using the Arrow format.
- type: UseCases
  data:
  - name: Analytics Data Exchange
    description: Share large analytical datasets between Python, R, Java, and other runtimes without serialization overhead.
  - name: Database Query Results
    description: Return query results from databases in Arrow format for fast analytics without Python/Java deserialization.
  - name: Data Pipeline Acceleration
    description: Accelerate ETL and data processing pipelines using columnar computation and SIMD optimizations.
  - name: Machine Learning Feature Stores
    description: Store and serve ML features in Arrow format for efficient batch and real-time feature retrieval.
  - name: High-Throughput Data Services
    description: Build high-throughput data microservices using Arrow Flight for efficient bulk data transfer over gRPC.
  - name: Cross-Language Data Sharing
    description: Share in-memory data between Python pandas/polars, Java, and Rust applications with zero-copy semantics.
- type: Integrations
  data:
  - name: Apache Parquet
    description: Native read/write support for Parquet columnar file format, the most common big data storage format.
  - name: Apache Spark
    description: Spark uses Arrow for Python UDF execution and pandas-on-Spark operations via PyArrow.
  - name: pandas
    description: Deep integration with pandas DataFrames via PyArrow's to_pandas() and from_pandas() conversions.
  - name: DuckDB
    description: DuckDB uses Arrow as its primary in-memory data format for zero-copy query result exchange.
  - name: Polars
    description: Polars DataFrame library is built on Arrow and supports zero-copy interop with Arrow arrays.
  - name: ADBC (Arrow Database Connectivity)
    description: Arrow Database Connectivity provides an Arrow-native database driver interface analogous to ODBC/JDBC.
  - name: Delta Lake
    description: Delta Lake integrates with Arrow for reading and writing Delta table data in columnar format.
  - name: Ray
    description: Ray distributed computing framework uses Arrow for shared-memory object storage between workers.
- url: https://arrow.apache.org/feed.xml
  type: Blog
maintainers:
- FN: Kin Lane
  email: info@apievangelist.com