Apache Flink vs Apache Beam - Which one is the right one for you?
Looking for a tool to help manage your big data workflow and guide your Cloud Architecture? Look no further than Apache Flink and Apache Beam, the two most popular streaming technologies today. However, which one should you use for your project? Let's compare them both and find out.
A brief introduction to Apache Flink and Apache Beam
First, let's give you an overview of what each tool does.
Apache Flink is an open-source stream processing framework that can handle complex processing of large data processors that have slightly different inputs/outputs. Flink's stream processing capability can often enable real-time processing and even changes the output based on the custom logic given.
Apache Beam is another open-source choice in the data streaming realm. Beam is particularly noted for its ability to process both batch and stream data. The latter feature is made possible by a Beam pipeline model that’s responsible for streaming data processing.
Performance: Apache Flink vs Apache Beam
Both Apache Flink and Apache Beam can perform extremely well in the right circumstances, but their performance varies.
When it comes to performance, Apache Flink boasts impressive numbers on benchmark tests. In fact, recent benchmarks have shown it to be up to five times quicker than Apache Beam, and for streaming and batch analytics, it regularly comes out on top.
However, Apache Beam offers a unique benefit in that its ability to work with batch processing can offer the technique advantages of stream processing, such as responsiveness and accuracy.
Scalability: Apache Flink vs Apache Beam
Both tools are quite scalable, meaning they can handle increasing workloads and data-processing challenges with ease. However, once again, Apache Flink has the edge here.
Apache Beam has a slight delay during processing, which can be problematic when working with high loads of data. Flink, in contrast, can manage and process a range of data sizes and can run on cluster resources for improved scalability, adaptability, and performance.
Ease of use: Apache Flink vs Apache Beam
If we're talking about the learning curve, then Apache Beam is more manageable than Apache Flink. It's a beginner-friendly technology and has a user-friendly set-up. It's also versatile and compatible, meaning it can integrate with any programming language.
However, once you get the hang of it, Apache Flink has sparked the interest of developers as it offers integrated support for high-level streaming patterns and SQL statements that support expressive processing, manipulation and analysis of real-time data.
Price: Apache Flink and Apache Beam
Both Apache Flink and Apache Beam are open-source and free to use. However, running them over the Cloud providers like Google Cloud, Azure or AWS will cost you according to their usage charges.
Conclusion
As you can see, both Apache Flink and Apache Beam have their strengths and weaknesses concerning managing workflows and building a reliable cloud architecture. Apache Flink seems to be a more powerful stream processing tool, with impressive scalability and strong performance. On the other hand, Apache Beam offers a lot more flexibility, thanks to its support for both batch and stream processing.
It's always best to determine what your specific needs are before settling on one of these technologies.
References
- Apache Flink vs. Apache Storm - Benchmarks
- Apache Beam vs. Apache Spark: Which is the better choice for running ETL jobs?
- Apache Beam vs Apache Flink: Which One Should You Choose?