Delta Lake vs Apache Flink: What are the differences?
Developers describe Delta Lake as "Reliable Data Lakes at Scale". An open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. On the other hand, Apache Flink is detailed as "Fast and reliable large-scale data processing engine". Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Delta Lake and Apache Flink belong to "Big Data Tools" category of the tech stack.
Some of the features offered by Delta Lake are:
- ACID Transactions
- Scalable Metadata Handling
- Time Travel (data versioning)
On the other hand, Apache Flink provides the following key features:
- Hybrid batch/streaming runtime that supports batch processing and data streaming programs.
- Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.
- Flexible and expressive windowing semantics for data stream programs
Delta Lake and Apache Flink are both open source tools. Apache Flink with 9.36K GitHub stars and 5.01K forks on GitHub appears to be more popular than Delta Lake with 1.26K GitHub stars and 210 GitHub forks.