Read this article to compare Apache NiFi vs Airflow vs Beam. At Bobcares, with our Server Management Services, we can handle your Apache issues.

Apache NiFi vs Airflow vs Beam

Apache NiFi, Apache Airflow, and Apache Beam are three open-source frameworks that specialize in data processing and workflow management. Let’s look into the details of each one.

1. Apache NiFi

• Data routing, transformation, and mediation are the main focuses of the data integration platform Apache NiFi.
• Designing and controlling data flows, as well as automating data transfer between different systems, becomes effortless with the help of a visual interface provided by data pipelines.
• Ingesting, processing, and real-time distribution of data from numerous sources are all made possible by NiFi.
• To handle different data formats, protocols, and transformations, it provides a large variety of processors.
• Additionally, NiFi also contains data provenance and security protections when comparing Apache NiFi vs Airflow vs Beam.

2. Apache Airflow

• A platform for creating, planning, and controlling workflows.
• Through the use of Directed Acyclic Graphs (DAGs), in which each node represents a task that may be carried out independently, we are able to build sophisticated workflows.
• In order to carry out various tasks, such as running scripts, conducting SQL queries, and interfacing with various systems and services, Airflow offers a broad range of operators.
• It provides a central web-based interface for managing workflows and monitoring them. It also supports functions like task dependencies, retries, and scheduling depending on the passage of time or uncontrollable occurrences.

3. Apache Beam

• Apache Beam creates pipelines for processing batch and streaming data.
• It also offers a portable API that may be used with many execution engines, such as Google Cloud Dataflow, Apache Flink, and Apache Spark.
• With the help of SDKs for Java, Python, Go, and other languages, Beam enables users to create data processing pipelines independent of the language they use.
• It manages the basic running details, including parallelism, fault tolerance, and data serialization. Also, offers a high-level abstraction for defining data changes.
• Building data processing pipelines that can use a variety of execution engines is a good use for Beam when considering Apache NiFi and Beam.

Overall Comparison

Data integration, routing, and actual data flow are the main areas of interest for Apache NiFi. Whereas, workflow orchestration, task scheduling, and monitoring are areas of mastery for Apache Airflow. A uniform model is made available by Apache Beam for creating batch and streaming data processing pipelines that can use different execution engines.

We can select one of these or a combination of them to meet the needs depending on the unique use case.

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Conclusion

The article provides a study from our Support team on Apache NiFi vs Airflow vs Beam. Users can select one of these or a combination of them to meet their specific needs.