Flink is a distributed processing engine and a scalable data analytics framework. You can use Flink to process data streams at a large scale and to deliver real-time analytical insights about your processed data with your streaming application.
The Future of Apache Flink
In essence, Flink is a stream processing engine designed for real-time data analysis, real-time risk control, and real-time ETL processing. But, in the future, the community hopes that Flink will continue to evolve into a full-fledged and unified data engine.
Apache Flink is an excellent choice to develop and run many different types of applications due to its extensive features set. Flink’s features include support for stream and batch processing, sophisticated state management, event-time processing semantics, and exactly-once consistency guarantees for state.
What Kafka streams?
Kafka Streams is a client library for building applications and microservices, where the input and output data are stored in an Apache Kafka® cluster. It combines the simplicity of writing and deploying standard Java and Scala applications on the client side with the benefits of Kafka’s server-side cluster technology.
Latency – No doubt Flink is much faster due to it’s architecture and cluster deployment mechanism, Flink throughput in the order of tens of millions of events per second in moderate clusters, sub-second latency that can be as low as few 10s of milliseconds.
Good integration with majority of data sources through Databricks Notebooks using Python, Scala, SQL, R. “The documentation is very good.” “With Flink, it provides out-of-the-box checkpointing and state management. With Flink, it provides guaranteed message processing, which helped us. …
This issue is unlikely to have any practical significance on operations unless the use case requires low latency (financial systems) where delay of the order of milliseconds can cause significant impact. That being said, Flink is pretty much a work in progress and cannot stake claim to replace Spark yet.
What is Cafca?
Kafka is an open source software which provides a framework for storing, reading and analysing streaming data. Being open source means that it is essentially free to use and has a large network of users and developers who contribute towards updates, new features and offering support for new users.
The name Flink was selected to honor the style of this stream and batch processor: in German, the word “flink” means fast or agile. A logo showing a colorful squirrel was chosen because squirrels are fast, agile and—in the case of squirrels in Berlin—an amazing shade of reddish-brown, as you can see in Figure 1-3.
Flink jobs consume streams and produce data into streams, databases, or the stream processor itself. Flink is commonly used with Kafka as the underlying storage layer, but is independent of it. … Flink clusters are highly available, and can be deployed standalone or with resource managers such as YARN and Mesos.