Top 8 Apache Airflow Alternatives in 2024

1

Apache Airflow

Apache Airflow is a workflow streamlining solution aiming at accelerating routine procedures. This article provides a detailed description of Apache Airflow as one of the most popular automation solutions. It also presents and compares alternatives to Airflow, their characteristic features, and recommended application areas. Based on that, each business could decide which workflow automation tool could benefit them.

#Workflows #Workflow Automation #Data Pipelines 66 social mentions

2

Skyvia

Skyvia offers the ETL, ELT, and Reverse ETL functionality for any data integration process. Set up source and destination data platforms or apps for indicating the data path. Then, determine how data needs to be transformed and mapped. Also, Skyvia allows scheduling data integration processes so that new or updated data is transferred regularly. While simple scenarios are delivered by Skyvia Import, more complex data-related tasks use Data Flow and Control Flow tools. They make it possible to involve multiple data connectors and complex data transformation scenarios.

#Data Integration #ETL #Web Service Automation 2 social mentions

3

Luigi

Even though Airflow and Luigi have much in common (open-source projects, Python used, Apache license), they have slightly different approaches to data workflow management. The first thing is that Luigi prevents tasks from running individually, which limits scalability. Moreover, Luigi’s API implements fewer features than that of Airflow, which might be especially difficult for new users.

#DevOps Tools #Workflow Automation #Workflows 9 social mentions

4

Prefect.io

Prefect, similarly to Airflow, is designed to help user orchestrate their workflows using Python. This service is web-based and could be easily set up with containerization tools, such as Docker, and deployed on the Kubernetes clusters. As a result, Prefect offers a high grade of scalability to its users, which might be of particular value to rapidly growing companies.

#Workflows #Workflow Automation #Data Integration

5

Dagster

Unlike Airflow, which supports any production environment, Dagster concentrates on cloud services and supports modern data stacks. Being cloud-native and container-native, this solution makes the scheduling and execution processes easier. Dagster was created with such specific goals in mind: designing ETL data pipelines, implementing machine learning curves, and managing data-driven systems.

#Utilities #Analytics #Analytics Integrator 2 social mentions

6

Apache NiFi

Another product by Apache is called NiFi – even though it’s also dedicated to data workflow management, it differs from Apache Airflow in many aspects. First of all, Apache NiFi is a completely web-based tool with a drag&drop interface and no coding. It’s easy to add and configure processors as graph nodes of data workflow, set up routing directions as graph edges, and indicate operations with data (filtering, joining, etc.).

#Analytics #Web Analytics #Mobile Analytics 17 social mentions

7

Azure Data Factory

While Apache Airflow focuses on creating tasks and building dependencies between them for workflow automation, Azure Data Factory is suitable for integration tasks. It would be a perfect fit for the construction of the ETL and ELT pipelines for data migration and integration across platforms.

#ETL #Data Integration #Workflow Automation 3 social mentions

8

Google Cloud Dataflow

Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.

#Big Data #Data Dashboard #Data Management 14 social mentions

9

AWS Step Functions

This service suits for many use cases, such as building ETL pipelines, orchestrating microservices, and managing high workloads. AWS Step Functions is particularly efficient when combined with other AWS solutions: Lambda for computing, Dynamo DB for storage, Athena for Analytics, SageMaker for machine learning, etc.

#Project Management #Workflow Automation #Web Service Automation 58 social mentions