Apache Iceberg

aid: apache-iceberg
name: Apache Iceberg
description: Apache Iceberg is an open table format for large analytic datasets that provides ACID transactions, schema evolution,
  hidden partitioning, and time travel. It works with Spark, Flink, Hive, Presto, Trino, DuckDB, ClickHouse, and many more
  compute engines. Governed by the Apache Software Foundation under the Apache 2.0 license.
type: Index
position: Consumer
access: 3rd-Party
image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
- ACID
- Analytics
- Apache
- Data Lake
- Lakehouse
- Open Source
- Table Format
created: '2026-03-16'
modified: '2026-05-19'
url: https://raw.githubusercontent.com/api-evangelist/apache-iceberg/refs/heads/main/apis.yml
specificationVersion: '0.19'
apis:
- aid: apache-iceberg:rest-catalog-api
  name: Apache Iceberg REST Catalog API
  description: The Iceberg REST Catalog API defines the specification for catalog server implementations, enabling table discovery,
    creation, metadata management, namespace management, and multi-table transactions over HTTP. It is the standard integration
    point for compute engines connecting to Iceberg catalogs.
  humanURL: https://iceberg.apache.org/rest-catalog-spec/
  tags:
  - Catalog
  - Namespace
  - REST
  - Table Format
  properties:
  - type: Documentation
    url: https://iceberg.apache.org/rest-catalog-spec/
  - type: OpenAPI
    url: openapi/apache-iceberg-rest-catalog-open-api.yaml
  - type: NaftikoCapability
    url: capabilities/rest-catalog-open-catalog-api.yaml
  - type: NaftikoCapability
    url: capabilities/rest-catalog-open-configuration-api.yaml
  - type: NaftikoCapability
    url: capabilities/rest-catalog-open-oauth2-api.yaml
- aid: apache-iceberg:java-api
  name: Apache Iceberg Java API
  description: The Iceberg Java API provides programmatic access to table operations, schema management, partition management,
    and catalog implementations. It is the primary library for integrating Iceberg with JVM-based compute engines including
    Spark, Flink, Hive, Trino, and Presto.
  humanURL: https://iceberg.apache.org/javadoc/latest/
  tags:
  - Java
  - JVM
  - SDK
  - Table Format
  properties:
  - type: Documentation
    url: https://iceberg.apache.org/javadoc/latest/
  - type: GettingStarted
    url: https://iceberg.apache.org/docs/latest/java-api-quickstart/
- aid: apache-iceberg:python-api
  name: PyIceberg Python API
  description: PyIceberg is the official Python implementation of the Apache Iceberg table specification. It provides programmatic
    access to Iceberg table metadata and data, with integrations for PyArrow, Pandas, DuckDB, Ray, Polars, and multiple catalog
    backends.
  humanURL: https://py.iceberg.apache.org/
  tags:
  - Python
  - SDK
  - Table Format
  properties:
  - type: Documentation
    url: https://py.iceberg.apache.org/
  - type: SDK
    url: https://pypi.org/project/pyiceberg/
  - type: GitHubRepository
    url: https://github.com/apache/iceberg-python
common:
- type: LinkedIn
  url: https://www.linkedin.com/company/apacheiceberg
- type: GitHubOrganization
  url: https://github.com/apache
- type: GitHubRepository
  url: https://github.com/apache/iceberg
- type: Documentation
  url: https://iceberg.apache.org/docs/latest/
- type: TermsOfService
  url: https://www.apache.org/licenses/LICENSE-2.0
- type: Blog
  url: https://iceberg.apache.org/blogs/
- type: YouTube
  url: https://www.youtube.com/@ApacheIceberg
- type: Versioning
  url: https://iceberg.apache.org/releases/
- type: ReleaseNotes
  url: https://iceberg.apache.org/releases/
- type: SpectralRules
  url: rules/apache-iceberg-spectral-rules.yml
- type: Vocabulary
  url: vocabulary/apache-iceberg-vocabulary.yaml
- type: Features
  data:
  - name: ACID Transactions
    description: Full ACID transaction support with serializable isolation for concurrent readers and writers.
  - name: Schema Evolution
    description: Add, drop, update, or rename columns without rewriting existing data files.
  - name: Hidden Partitioning
    description: Automatic partition management that prevents common user mistakes and silently incorrect results.
  - name: Partition Evolution
    description: Change partition layout over time without rewriting existing data.
  - name: Time Travel
    description: Query historical snapshots of tables and roll back to any prior version.
  - name: Row-Level Updates
    description: Supports upserts, deletes, and updates at the row level via merge-on-read and copy-on-write modes.
  - name: Multi-Engine Support
    description: Works with Spark, Flink, Hive, Trino, Presto, Impala, DuckDB, ClickHouse, and more.
  - name: Cloud-Native Storage
    description: Native support for S3, ADLS, GCS, and HDFS with no filesystem dependencies.
- type: UseCases
  data:
  - name: Lakehouse Analytics
    description: Build open lakehouse architectures with ACID guarantees across petabyte-scale datasets.
  - name: Real-Time Data Pipelines
    description: Stream data into Iceberg tables via Flink or Kafka Connect with exactly-once semantics.
  - name: Data Versioning and Auditing
    description: Use time travel to audit historical data states and implement regulatory compliance.
  - name: Multi-Engine Query Federation
    description: Query the same Iceberg tables from multiple engines (Spark, Trino, DuckDB) without data duplication.
  - name: Cloud Data Migration
    description: Migrate on-premises Hive workloads to cloud-native Iceberg tables with full compatibility.
- type: Integrations
  data:
  - name: Apache Spark
    description: Full read/write support for Iceberg tables in Spark batch and streaming workloads.
  - name: Apache Flink
    description: Streaming and batch integration with exactly-once write support.
  - name: Apache Hive
    description: Read and write Iceberg tables from Hive queries using the Iceberg Hive integration.
  - name: Trino
    description: Query Iceberg tables from Trino with full partition pruning and predicate pushdown.
  - name: AWS Glue Catalog
    description: Use AWS Glue as the Iceberg catalog backend with full metadata management.
  - name: AWS Athena
    description: Query Iceberg tables stored in S3 using Amazon Athena.
  - name: Project Nessie
    description: Git-like catalog branching and versioning via Nessie catalog integration.
  - name: DuckDB
    description: Local analytics on Iceberg tables via the DuckDB Iceberg extension.
  - name: ClickHouse
    description: Query Iceberg tables from ClickHouse via the ClickHouse Iceberg integration.
  - name: Snowflake
    description: Access Iceberg tables managed in Snowflake's Polaris catalog.
  - name: Google BigQuery
    description: Use BigQuery as a compute engine over Iceberg tables with BigLake Metastore.
  - name: Databricks
    description: Create and query Iceberg tables on Databricks using Unity Catalog.
- type: Integrations
  url: https://iceberg.apache.org/integrations/
integrations:
- name: amoro/
- name: daft/
- name: risingwave/
maintainers:
- FN: Kin Lane
  email: [email protected]