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AWS Glue vs Google Cloud Dataflow - Which ETL Tool is Better?

January 20, 2022

Introduction

Data ingestion is a crucial step when building big data applications. This process is commonly known as Extract, Transform, and Load (ETL). Many companies have moved their ETL jobs to the cloud, leveraging cloud-based ETL tools. In this blog, we'll compare AWS Glue and Google Cloud Dataflow, two popular ETL tools used in Cloud Computing.

AWS Glue

AWS Glue is an ETL tool offered by Amazon Web Services (AWS). It provides a managed service that crawls data sources, extracts the metadata, and creates the ETL job. There's no need to provision or manage any computing resources. AWS Glue uses Apache Spark as the underlying engine, which enables the tool to provide a serverless data preparation environment.

Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud-based ETL tool provided by Google Cloud Platform. It offers a pipeline-as-a-service platform for batch and stream data processing. It uses Apache Beam as the programming model, which allows you to build data pipelines that can run on different execution engines.

Comparison

Performance

When comparing the performance of AWS Glue and Google Cloud Dataflow, it's important to note that both are fast and efficient ETL tools. However, according to a benchmark conducted by Datamation, AWS Glue was found to outperform Google Cloud Dataflow by more than 50% in a specific use case.

Cost

Both AWS Glue and Google Cloud Dataflow use a pay-as-you-go pricing model. However, AWS Glue has a more cost-effective pricing model due to its serverless nature. With AWS Glue, you only pay for what you use, so if you're not running an ETL job, you're not paying for it. With Google Cloud Dataflow, you pay for the number of virtual machine (VM) instances running in your data processing job.

Ease of Use

AWS Glue is more effortless to use than Google Cloud Dataflow due to its graphical user interface. AWS Glue also has pre-built data connectors that enable you to connect to data sources, whereas Google Cloud Dataflow requires you to write your own custom code to connect to data sources.

Conclusion

Now that we've compared AWS Glue and Google Cloud Dataflow, we can conclude that both are powerful ETL tools. When choosing between the two tools, consider your business's requirements, including performance, cost, and ease of use.

References

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