Apache Delta Lake vs Apache Hudi
When we talk about big data technologies, one cannot ignore the power of Apache Delta Lake and Apache Hudi. These technologies are like the gladiators of the big data world, fighting to claim the top spot. In this comparison article, we will take an unbiased look at the features, performance, and use cases of both these technologies.
What is Apache Delta Lake?
Apache Delta Lake is an open-source storage layer designed to bring reliability to data lakes. It provides features like ACID transactions, schema enforcement, and schema evolution to your big data lake. Delta Lake is built on top of Apache Spark and can handle both batch and streaming workloads. It also supports data-manipulation commands like DELETE and UPDATE, making it a perfect fit for data warehousing and data lake use cases.
What is Apache Hudi?
Apache Hudi is an open-source data management framework designed to simplify the way developers work with big data. It provides features like ACID transactions, record-level insert, update, and delete. Hudi is built on top of Apache Spark and is designed to handle complex big data workloads that involve real-time performance, incremental data loads, and large-scale batch processing. It supports both stream and batch ingestion.
Comparison between Apache Delta Lake and Apache Hudi
Both these technologies share similar features like ACID transactions and schema enforcement. However, there are few points of differences that set them apart.
Performance
When it comes to performance, Delta Lake has an edge over Hudi in some cases. Delta Lake's optimization techniques, like Z-Ordering, can speed up queries by a significant margin. Hudi's query speeds can be slower in some scenarios due to the architecture of the framework.
Use cases
Delta Lake is a perfect fit for Data Warehouse and analytics use cases. Its support for DELETE and UPDATE commands makes it easy to build incremental data pipelines, and its schema enforcement features ensure data quality. Hudi, on the other hand, is more suited for an operational data store or real-time use cases, where updates and deletes of individual records are a requirement.
Community Support
Both Delta Lake and Hudi have active communities, but Delta Lake has been gaining traction faster than Hudi. Also, Delta Lake has better integration with other big data tools like AWS Glue and Databricks.
Conclusion
In conclusion, we can say that both Apache Delta Lake and Apache Hudi are powerful technologies designed to handle big data workloads. Both have different strengths, and it depends on your use case to decide which technology is better suited for you. Delta Lake is the best fit for data warehousing and analytics use cases, whereas Hudi is more suited for operational data stores and real-time use cases.
So, if you are planning to implement a big data pipeline, both these technologies are worth considering. As always, we recommend doing your own research and evaluating both technologies based on your specific requirements.
References
- Delta Lake: https://delta.io/
- Hudi: https://hudi.apache.org/
- Delta Lake vs Hudi: https://towardsdatascience.com/delta-lake-vs-apache-hudi-whats-the-better-choice-a7f8edcf0da7
- Delta Lake and Hudi comparison: https://www.linkedin.com/pulse/hudi-vs-delta-lake-ulrike-wienh%C3%B6fer/