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APACHE ICEBERG
High-performance table format for analytic data lakes
Apache-2.0
ABOUT
Data lakes built on object storage like S3 lack ACID transactions, schema enforcement, and consistent snapshots, making reliable analytics and ML data pipelines difficult to maintain. Apache Iceberg provides a high-performance table format that adds SQL-like transactional guarantees, time-travel queries, schema evolution, and partition evolution on top of existing data lakes, enabling multiple query engines to operate on the same data safely and concurrently.
INSTALL
pip install pyicebergINTEGRATION GUIDE
1. Build reliable lakehouse architectures with ACID transactions and consistent snapshots on object storage
2. Run concurrent analytical workloads from Spark, Trino, Flink, and Hive on the same tables without data corruption
3. Enable time-travel queries for ML training data versioning, auditing, and rollback
4. Evolve table schemas and partition layouts without rewriting data or blocking reads and writes
TAGS
data-laketable-formatparquetanalyticsbig-dataapachepython