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Apache Iceberg

The open table format that brings ACID transactions and schema evolution to the data lake.

Apache Iceberg is an open table format for analytic datasets on object storage (S3, GCS, Azure): a metadata layer over Parquet or ORC files that adds ACID transactions, schema and partition evolution without rewrites, and snapshots for time travel and rollback. Spark, Trino, Flink, Snowflake, BigQuery, Athena and DuckDB read and write the same tables through a shared catalog (REST, Glue, Nessie). It's our choice when a lakehouse must stay vendor-independent while guaranteeing data reliability.

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[ Why Apache Iceberg ]

What Apache Iceberg brings to your project.

Typical use cases: Open multi-engine lakehouse, migration off proprietary warehouses, data history and auditing.

01
ACID transactions on object storage: consistent reads, safe concurrent writes.
02
Schema and partition evolution without rewriting the data.
03
Snapshots: time travel, rollback and an audit trail for every table version.
04
Multi-engine: Spark, Trino, Flink, Snowflake and BigQuery on the same tables.

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A project with Apache Iceberg?

Describe your project. Our team replies within 24 hours with free technical scoping, along with a clear estimate of costs and timelines. No commitment.

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