Item: Apache Flink
Rating: 9
Author: Verified User

Use Cases and Deployment Scope

Apache Flink is employed within our company exclusively in our real-time data pipeline. Apache Flink stands out as one of the few frameworks capable of providing the scalable and distributed processing we require while ensuring the integrity and fault tolerance of our pipeline through its built-in systems. Without Apache Flink, we might struggle to get valuable insights and benefits to our business.

Pros and Cons

Low latency Stream Processing, enabling real-time analytics
Scalability, due its great parallel capabilities
Stateful Processing, providing several built-in fault tolerance systems
Flexibility, supporting both batch and stream processing

Python/SQL API, since both are relatively new, still misses a few features in comparison with the Java/Scala option
Steep Learning Curve, it's documentation could be improved to something more user-friendly, and it could also discuss more theoretical concepts than just coding
Community smaller than other frameworks

Return on Investment

Allowed for real-time data recovery, adding significant value to the busines
Enabled us to create new internal tools that we couldn't find in the market, becoming a strategic asset for the business
Enhanced the overall technical capability of the team

Alternatives Considered

Apache Spark

Apache Spark is more user-friendly and features higher-level APIs. However, it was initially built for batch processing and only more recently gained streaming capabilities. In contrast, Apache Flink processes streaming data natively. Therefore, in terms of low latency and fault tolerance, Apache Flink takes the lead. However, Spark has a larger community and a decidedly lower learning curve.

Key Insights

Do you think Apache Flink delivers good value for the price?

Yes

Are you happy with Apache Flink's feature set?

Yes

Did Apache Flink live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Apache Flink go as expected?

Yes

Would you buy Apache Flink again?

Yes

Other Software Used

ClickHouse, Slack, Snowflake

Likelihood to Recommend

In well-suited scenarios, I would recommend using Apache Flink when you need to perform real-time analytics on streaming data, such as monitoring user activities, analyzing IoT device data, or processing financial transactions in real-time. It is also a good choice in scenarios where fault tolerance and consistency are crucial. I would not recommend it for simple batch processing pipelines or for teams that aren't experienced, as it might be overkill, and the steep learning curve may not justify the investment.

Unrivaled Excellence in Streaming Processing and Fault Tolerance

Overall Satisfaction with Apache Flink