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Daft
Daft Daft is a distributed query engine written in Python and Rust, two fast-growing ecosystems in the data engineering and machine learning industry. It exposes its flavor of t... -
Apache Spark
Querying from Apache Spark To read an Apache XTable™ (Incubating) synced target table (regardless of the table format) in Apache Spark locally or on services like Amazon EMR, Goog... -
Queries
Spark Queries To use Iceberg in Spark, first configure Spark catalogs . Iceberg uses Apache Spark’s DataSourceV2 API for data source and catalog implementations. Querying with S... -
StarRocks
Querying from StarRocks StarRocks allows you to query table formats like Hudi, Delta and Iceberg tables using our external catalog feature. Users do not need additional configura... -
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 -
Google BigQuery
Querying from Google BigQuery Iceberg tables To read an Apache XTable™ (Incubating) synced Iceberg table from BigQuery , you have two options: Using Iceberg JSON metadata file ... -
JDBC
Iceberg JDBC Integration JDBC Catalog Iceberg supports using a table in a relational database to manage Iceberg tables through JDBC. The database that JDBC connects to must suppo... -
Impala
https://impala.apache.org/docs/build/html/topics/impala_iceberg.html -
Snowflake
Querying from Snowflake Currently, Snowflake supports Iceberg tables through External Tables and also Native Iceberg Tables . Iceberg on Snowflake is currently supported in pub... -
Reliability
Reliability Iceberg was designed to solve correctness problems that affect Hive tables running in S3. Hive tables track data files using both a central metastore for partitions a...
