AWS Data Pipeline vs AWS Glue: Which Tool is Right for You?

If you’ve landed here because you want a comparison of AWS Data Pipeline vs AWS Glue, you may be in for a surprise. The landscape of Amazon Web Services (AWS) data services is changing. But this is nothing unusual. With more than 200 service offerings, AWS is continually coming up with new and improved ways to perform the same tasks. Sometimes, these methods will remain available indefinitely. Other times, as in the case of AWS Data Pipeline, older services are gradually phased out in favor of better solutions.

Modern data orchestration solutions on AWS include Glue, Step Functions, and a service called Managed Workflows for Apache Airflow (MWAA). Let’s take a look at this evolution in some detail, starting with AWS Pipeline.

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The Legacy of AWS Data Pipeline

If you were thinking of creating a new service using AWS Data Pipeline, think again. We’ll let AWS explain it for us:

“After careful consideration, we have made the decision to close new customer access to AWS Data Pipeline, effective July 25, 2024. AWS Data Pipeline existing customers can continue to use the service as normal. AWS continues to invest in security, availability, and performance improvements for AWS Data Pipeline, but we do not plan to introduce new features.”

They go on to tell us that Data Pipeline has been “a foundation service” for extract, transform, and load (ETL) solutions for customers but that there is a need for “a more feature-rich platform.” That’s particularly true given the rapid growth of machine learning (ML) and the development of artificial intelligence (AI) innovations that it supports.

The initial release of AWS Data Pipeline was in December 2012. It was designed to automate data movement between on-premises data centers and the AWS cloud. Data Pipeline supports various data sources and destinations, including S3, RDS, DynamoDB, Redshift, and on-premises databases. 

While its many features have made it a robust ETL solution for more than a decade, It just isn’t enough to handle the sophisticated workloads of modern cloud data environments.

Migration Path from Data Pipeline

For those currently on AWS Data Pipeline, AWS has laid out a migration path to a more modern, serverless architecture. There’s no indication when the service will be phased out entirely, but users are advised to make plans to migrate to another service at some point. 

Advantages of such a move include better support for complex transformations, improved integration with other AWS services, and automated resource management.

Migrating from the AWS Data Pipeline begins with a comprehensive assessment of existing workflows to determine the most suitable target service. You’ll need to map current functionalities to new service features, establish a timeline, and create a detailed migration strategy. The whole process should involve rigorous testing and validation of data integrity and workflow reliability.

Modern AWS Data Orchestration Solutions: AWS Glue

AWS Glue is a fully managed data integration service that does not require any management or provisioning of infrastructure. As with the rest of their serverless portfolio, AWS handles all that. 

AWS Glue is designed for data analytics and machine learning, and it’s a perfect platform for application development. It supports more than 70 data source types, and it automatically scales based on the workload. Users pay only for the resources consumed. AWS components include:

• Data catalog

• ETL engine

• Workflow management

(Source: AWS Glue Concepts)

Visual ETL Development

For us humans, it helps if we can visualize processes rather than confine ourselves to text-based descriptions. With AWS Glue Studio, you can see graphical representations of your designed ETL jobs before you execute them. The platform has more than 250 built-in data transformations available, and it is a great environment for interactive development and testing. AWS Glue uses Apache Spark for its processing engine.

Built-in Job Scheduling and Monitoring

AWS Glue includes built-in event-driven ETL pipeline triggers and allows for flexible job scheduling. Capabilities include:

 Job performance dashboards with:

• Automatic error handling

• Run time metrics collection

• Real-time monitoring

• Time-based and event-based triggers

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AWS Step Functions: Features and Capabilities 

When considering data transformation options on AWS, we should not overlook a serverless function orchestrator that has been around since 2016. AWS Step Functions offers both standard workflows for long-running processes and express workflows for high-volume, short-duration tasks. 

Other capabilities include built-in error handling, state management and execution tracking, and parallel processing. You can think of Step Functions as similar to the business workflows you’ve seen at the office. 

Integration with AWS Services

It’s definitely a plus that AWS Step Functions has direct integrations with more than 220 AWS services. That alone is a big selling point. Rather than choosing between Step Functions and Glue, you can actually leverage Step Functions to enhance your Glue ETL processes. This diagram from the AWS website shows just how that could work:

[Source: AWS Big Data Blog]

Use Cases Best Suited for Step Functions

There are probably a million use cases for AWS Step Functions. As far as data processing workflows are concerned, common use cases include:

• ETL pipeline orchestration

• Large-scale data transformations

• Data validation and quality checks

• Parallel data processing

That’s not to mention all the other things you can do with Step Functions, such as machine learning, data lake operations, and microservice orchestration. It’s the perfect complement for AWS Glue. And it helps fill in the gaps with so many other AWS services.

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Amazon MWAA

Amazon Managed Workflows for Apache Airflow (MWAA) is a managed workflow orchestration service for Apache Airflow. It’s available for those who want to use their current Apache Airflow platform to orchestrate their workflows. MWAA comes with a lot of pre-built operators and includes extensive plugin support. 

Features include:

• Enterprise scaling

• Python-based workflow definitions

• Native CloudWatch integration

• Built-in security

• Support for custom plugins

Choosing the Right Modern Solution

Since AWS has a selection of data orchestration solutions, the question is how to decide the best one for your situation. Let’s start with two of them that we can consider limited by their very nature. If you don’t have AWS Data Pipeline already, that choice is ruled out because they are taking no more customers. The use of MWAA might be naturally confined to those who are bringing their existing Apache Airflow workloads to the cloud.

As for AWS Glue and AWS Step Functions, this may not be a question of “either/or.” Since both services fit together hand in glove, you may want to implement them both in your AWS infrastructure. 

When considered separately, you should know that AWS Glue is best for ETL workloads. Its serverless architecture and visual development tools make it a good choice. AWS Step Functions, on the other hand, is ideal for complex, state-machine workflows.

Here is a summary to help you make your choice:

Future-Proofing Your Data Architecture

Going forward, it’s a good idea to become familiar with best practices for AWS data orchestration. These include the implementation of modular, loosely coupled designs, going serverless where appropriate, and using repeatable infrastructure as code (IaC) configurations rather than tedious console-based updates. As for security, the use of Amazon’s Key Management Service (KMS) is a good idea, as well as robust Identity and Access Management (IAM) policies.

Since things change so quickly, you’ll need to stay current on the evolution of AWS services, including data orchestration. The innovations keep coming fast and furious, and if you’re not careful, you might miss something very important to your existing or future cloud infrastructure.

Conclusion

Managing data can be overwhelming, but AWS can help you get it under control. A data move and transformation that might have taken a month in a traditional IT architecture can be reduced to days or even hours with the right AWS data orchestration service. While Data Pipeline may not be available for new customers, AWS Glue, Step Functions, or MWAA can likely do all that you need. Every aspiring IT professional needs to keep up with the latest and greatest solutions. Nobody wants to be left behind.

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