Apache Flink vs Kafka: What are the differences?
Apache Flink: 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; Kafka: Distributed, fault tolerant, high throughput pub-sub messaging system. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Apache Flink and Kafka are primarily classified as "Big Data" and "Message Queue" tools respectively.
Some of the features offered by Apache Flink are:
- 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
On the other hand, Kafka provides the following key features:
- Written at LinkedIn in Scala
- Used by LinkedIn to offload processing of all page and other views
- Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
"Unified batch and stream processing" is the top reason why over 6 developers like Apache Flink, while over 95 developers mention "High-throughput" as the leading cause for choosing Kafka.
Apache Flink and Kafka are both open source tools. Kafka with 12.7K GitHub stars and 6.81K forks on GitHub appears to be more popular than Apache Flink with 9.35K GitHub stars and 5K GitHub forks.
Uber Technologies, Spotify, and Slack are some of the popular companies that use Kafka, whereas Apache Flink is used by Zalando, sovrn Holdings, and BetterCloud. Kafka has a broader approval, being mentioned in 509 company stacks & 470 developers stacks; compared to Apache Flink, which is listed in 20 company stacks and 22 developer stacks.