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Schemas
Iceberg tables support the following types: Type Description Notes boolean True or false int 32-bit signed integers Can promote to long long 64-bit s... -
Mixed-Hive
Mixed-Hive format is a format that has better compatibility with Hive than Mixed-Iceberg format. Mixed-Hive format uses a Hive table as the BaseStore and an Iceberg table as the C... -
Amazon Athena
To read a OneTable synced target table (regardless of the table format) in Amazon Athena, you can create the table either by: Using a DDL statement as mentioned in the following... -
Hive
Hive Iceberg supports reading and writing Iceberg tables through Hive by using a StorageHandler . Feature support The following features matrix illustrates the support for diff... -
Nessie
Iceberg Nessie Integration Iceberg provides integration with Nessie through the iceberg-nessie module. This section describes how to use Iceberg with Nessie. Nessie provides seve... -
Flink Getting Started
Flink Apache Iceberg supports both Apache Flink ‘s DataStream API and Table API. See the Multi-Engine Support page for the integration of Apache Flink. Feature support Flink... -
Kafka Connect
Kafka Connect Kafka Connect is a popular framework for moving data in and out of Kafka via connectors. There are many different connectors available, such as the S3 sink for writ... -
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Connectors for Spark SQL Query Engine
Delta Lake Delta Lake with Microsoft Azure Blob Storage Hudi Iceberg Kudu Hive Apache Paimon (Incubating) TiDB TPC-DS TPC-H -
Creating your first interoperable table
Creating your first interoperable table Using Apache XTable™ (Incubating) to sync your source tables in different target format involves running sync on your current dataset usi...
