Review:
Apache Hudi
overall review score: 4.2
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score is between 0 and 5
Apache Hudi (Hadoop Upserts Deletes and Incrementals) is an open-source data management framework designed to simplify the process of building incremental data pipelines on large-scale datasets stored in Hadoop-compatible data lakes. It provides functionalities for streaming data ingestion, upsert and delete operations, and efficient data versioning, enabling real-time analytics and data freshness.
Key Features
- Incremental data ingestion from streaming sources
- Support for upsert and delete operations on large datasets
- ACID transactions to ensure data consistency
- Data versioning and time travel capabilities
- Integration with Apache Spark, Hive, Presto, and other big data tools
- Efficient storage optimization through compaction and clustering
- Schema evolution support
Pros
- Enables real-time and near-real-time analytics with efficient incremental updates
- Supports ACID transactions for reliable data operations
- Flexible integration with major big data processing frameworks
- Facilitates complex data management tasks like deletions and updates in data lakes
- Open source with active community support
Cons
- Steep learning curve for new users unfamiliar with big data ecosystems
- Requires careful configuration for optimal performance
- Managing compaction processes can add complexity to workflows
- Less mature compared to traditional databases; potential scalability challenges in very large deployments