Apache Hudi

Apache Hudi is an open-source data lakehouse platform designed to bring database-like functionality to data lakes. It enables efficient, incremental data processing with ACID guarantees, time travel, and schema evolution. Built on a high-performance open table format, Hudi supports both streaming and batch workloads, making it ideal for modern data infrastructure.

Features

• Support for mutability across all workload types
• Fast, pluggable indexing for updates and deletes
• Incremental data processing for low-latency analytics
• ACID transactional guarantees with snapshot isolation
• Time travel capabilities for historical data analysis
• Multi-cloud ecosystem compatibility
• Automated table services for clustering, compaction, and cleaning
• Multi-modal indexing for query acceleration
• Schema evolution and enforcement for resilient pipelines

Capabilities

• Efficient upserts and deletes for CDC and streaming data
• Integration with popular engines like Spark, Flink, Hive, Presto, and Trino
• Support for open data formats and cloud-native environments
• Auto-ingestion from sources like Kafka and Debezium
• Auto-sync with cloud data catalogs
• Native Rust implementation (Hudi-rs) with Python bindings
• Optimized file layout and table types (Copy-on-Write, Merge-on-Read)
• Snapshot, incremental, and read-optimized query modes

Benefits

• Accelerated data ingestion and processing
• Reduced operational complexity with automated services
• Improved data reliability and consistency
• Enhanced query performance on large datasets
• Flexibility to adapt to evolving data schemas
• Proven scalability in production environments
• Active open-source community and continuous innovation