AWS Data Pipeline [EOL] vs AWS Glue comparison

AWS Data Pipeline [EOL] and AWS Glue are both solutions in the Cloud Data Integration category. Additionally, 100% of AWS Data Pipeline [EOL] users are willing to recommend the solution, compared to 90% of AWS Glue users who would recommend it.

AWS Data Pipeline [EOL]

Read 2 AWS Data Pipeline [EOL] reviews

100% willing to recommend

AWS Glue

Read 50 AWS Glue reviews

9,204 Views
6,903 Comparison Views

90% willing to recommend

AWS Data Pipeline [EOL]

AWS Glue

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Executive Summary

We performed a comparison between AWS Data Pipeline [EOL] and AWS Glue based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration.

To learn more, read our detailed Cloud Data Integration Report (Updated: July 2026).

Buyer's Guide

Cloud Data Integration

July 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AWS Data Pipeline [EOL]

Average Rating

8.0

Number of Reviews

Ranking in other categories

No ranking in other categories

AWS Glue

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

Cloud Data Integration (1st)

Featured Reviews

BarathwajRamamoorthy

Senior Director Data Architecture at Managed Markets Insight & Technology, LLC

A tool with great orchestration and development capabilities but needs to improve its user-defined functions

In the tool, parallel processing is an area that is contingent, in the sense that you have to be watchful for the cap that you have in terms of computing behind AWS Data Pipeline. You need to always watch for some reason. I am capped with 200 nodes, and if I get to use more than 200 nodes, the AWS Data Pipeline will fail. AWS doesn't state that I have almost gone beyond my limits, and it is allowing me now to go beyond the set limits if I talk to a representative and figure it out. Such aforementioned warnings are not let out by AWS, and they end up failing the nodes if I go beyond the set cap limits.

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Nivas Srinivasan

Principal Consultant at a retailer with 1,001-5,000 employees

The solution improves ETL performance but faces challenges with version upgrades

For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless. It is serverless, so I do not need to worry about other integrations. It runs on a serverless VM. Glue services from AWS are regularly upgraded with new properties and functions. We use PySpark and other frameworks, which help customize our ETL process in a standard way. During our process, we utilized the typical SQL ITIL process standard in Glue-oriented ETL services, which helped us improve performance and time. AWS running time, mostly during the morning, saved us time compared to the old ETL method. There are many email notifications once a job is successful or fails, and we get notifications using SES or AWS's Simple Notification Service. Glue is integrated with both email alerts, and we are responsible for managing the full data journey from end to end.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable feature of the solution is that orchestration and development capabilities are easier with the tool."

"It is a stable solution...It is a scalable solution."

"If I'm working with big data, common languages like Python work quite nicely, which is advantageous."

"The solution is highly user-friendly, and its features are easy to use. The new addition of AWS Glue Data Catalog is also very beneficial, making the tool even more helpful for its users."

"You do not need many frameworks to run Glue."

"It's very good to manage."

"The solution helps organizations gain flexibility in defining the structure of the data."

"I also like that you can add custom libraries like JAR files and use them. So, the ability to use a fast processing engine and embed basic jobs easily are significant advantages."

"The most valuable feature of AWS Glue is its ease of use and good documentation. Additionally, we can do all the transformations that we need."

"The most valuable feature for me is the visual interface of AWS Glue."

More AWS Glue pros

Cons

"It's almost semi-automatic because you must review and approve code push, which works well. Still, we had many problems getting there during the deployment process, but we got there."

"The user-defined functions have shortcomings in AWS Data Pipeline."

"The solution’s stability could be improved."

"AWS Glue would be improved by making it easier to switch from single to multi-cloud."

"The crucial problem with AWS Glue is that it only works with AWS."

"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."

"It would be better if it were more user-friendly."

"I would like to see stable libraries at the moment they are not there."

"The price of the solution could improve."

"In the building and deployment aspects, there is room for improvement. The current process is a bit complicated and could benefit from being more user-friendly and simpler, which would help speed up the deployment process."

More AWS Glue cons

Pricing and Cost Advice

"The way we use it, I think it is fair as we're getting a good value for money compared to having a server or some other data pipeline."

"I rate the pricing between six to eight on a scale from one to ten, where one is low price, and ten is high price."

"AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill."

"It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."

"This solution is affordable and there is an option to pay for the solution based on your usage."

"I would rate the solution a six or seven on a scale of one to ten, with ten being very expensive. Specifically, I rate its pricing a six out of ten."

"If you are using the solution for an enterprise business, it will be expensive."

"I rate the product's pricing a five on a scale of one to ten, where one is a high price, and ten is a low price."

"AWS Glue is quite costly, especially for small organizations."

"The pricing is a bit higher than other solutions like Athena and EC2. If the pricing becomes more scaled or flexible, it will be good because you have to pay 44 cents just for one DPU for an hour. If you increase DPUs to 5 or 10, the pricing gets multiplied. There are also some time limits like 0 to 10 minutes or 10 to 20 minutes. If the pricing is according to the minutes, it would be better because you have to limit your job to 10 minutes or 20 minutes."

More AWS Glue pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

20%

Manufacturing Company

Computer Software Company

Comms Service Provider

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	34

Questions from the Community

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How do you select the right cloud ETL tool?

AWS Glue and Azure Data factory for ELT best performance cloud services.

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We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in...

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What are the most common use cases for AWS Glue?

AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or ma...

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Comparisons

IBM InfoSphere DataStage vs AWS Data Pipeline [EOL]

Compared 27% of the time

Perspectium DataSync vs AWS Data Pipeline [EOL]

Compared 23% of the time

MuleSoft Composer vs AWS Data Pipeline [EOL]

Compared 20% of the time

More AWS Data Pipeline [EOL] Competitors

AWS Database Migration Service vs AWS Glue

Compared 41% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 6% of the time

SSIS vs AWS Glue

Compared 4% of the time

Palantir Foundry vs AWS Glue

Compared 3% of the time

Amazon Data Firehose vs AWS Glue

Compared 3% of the time

More AWS Glue Competitors

Product Reports

Buyer's Guide

Cloud Data Integration

July 2026

Download AWS Data Pipeline [EOL] product report

Buyer's Guide

AWS Glue

August 2026

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Overview

AWS Data Pipeline is a web service that helps you reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals. ... AWS Data Pipeline also allows you to move and process data that was previously locked up in on-premises data silos.

Amazon Web Services (AWS)

AWS Glue is a serverless data integration service offering seamless integration with AWS services like S3, Redshift, and Athena. Known for its flexibility with data formats and automation of ETL tasks, AWS Glue enhances data management and transformation.

AWS Glue facilitates seamless data extraction, transformation, and loading for businesses, integrating with key AWS services, allowing efficient data pipeline automation. It's valued for a user-friendly GUI, scalability, and cost-effectiveness, supporting PySpark for complex datasets and includes a robust data catalog, real-time backup capabilities, and code generation. Despite its strengths, improvements are needed in documentation, training, and broader programming language support. Users face challenges with its complex interface and integration with non-AWS products, driving demand for enhancements in its usability and performance.

What are AWS Glue's most important features?

Seamless AWS Integration: Connects effortlessly with services like S3, Redshift, and Athena.
Serverless Operation: Removes the need for infrastructure management.
Flexible Data Format Handling: Supports various data formats for comprehensive data management.
User-Friendly GUI: Simplifies the creation and management of ETL jobs.
Data Catalog: Provides an organized repository for metadata management.
Real-Time Data Backup: Ensures data integrity and availability.
Code Generation: Facilitates easy script generation for data processes.

What benefits or ROI should users look for in reviews?

Cost Efficiency: Reduced operational costs through serverless architecture.
High Performance: Efficient data processing and transformation capabilities.
Scalability: Adapts to businesses' evolving data demands.
Ease of Use: Intuitive interface allowing streamlined ETL workflows.
Automation: Simplified data pipeline tasks saving time and effort.

Businesses leverage AWS Glue in industries for ETL processes, data integration, and transformation. It is used to optimize data lakes or warehouses integration, enhancing data cataloging and real-time integration. Its serverless feature enables efficient data processing in sectors like finance and healthcare, where handling complex data-intensive tasks is crucial.

Amazon Web Services (AWS)

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Buyer's Guide

Cloud Data Integration

July 2026

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