AWS Data Pipeline [EOL] vs AWS Glue comparison

Why PeerSpot?

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

9,651 Views
7,335 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: September 2026).

Buyer's Guide

Cloud Data Integration

September 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."

"AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models."

"One of the best features of the solution is its ability to easily integrate with other AWS services."

"Data catalog and triggers are the two best features for me. AWS Glue has its own data catalog, which makes it great and really easy to use. Triggers are also really good for scheduling the ETL process."

"The solution is serverless so it allows us to transform data while optimizing the cost and performance of Spark jobs."

"One aspect that I would like to highlight is the Glue Crawler, which we utilize when working with large datasets to ensure the schema updates seamlessly without requiring end-team knowledge."

"It is a stable and scalable solution."

"AWS Glue is quite better than other tools, but you have to learn it properly before you start using it."

"The two features I find most valuable in AWS Glue are its user interface and ease of use."

More AWS Glue pros

Cons

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

"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."

"Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding."

"I would like to see a more robust interface on the no-code side. This would be nice to be able to split cells."

"The price of the solution could improve."

"The setup and installation is a bit complex without advanced knowledge or training."

"On occasion, the solution's dashboard reports that a project failed due to runtime but it actually succeeded."

"The technical support for this solution could be improved. In future, we would like to connect more services like Athena or Kinesis to help control more loads of data."

"If there's a cluster-related configuration, we have to make worker notes, which is quite a headache when processing a large amount of data."

"The solution’s stability could be improved."

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."

"The solution's pricing is based on DPUs so it is a good idea to optimize use or it can get expensive."

"The current cost is around forty to fifty thousand a month."

"I rate the tool an eight on a scale of one to ten, where one is expensive, and ten is expensive."

"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."

"The overall cost of AWS Glue could be better. It cost approximately $1,000 a month. There is paid support available from AWS Glue."

"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."

"Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."

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

More AWS Glue pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

18%

Manufacturing Company

Comms Service Provider

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	12
Midsize Enterprise	5
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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How does Talend Open Studio compare with AWS Glue?

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 18% of the time

Perspectium DataSync vs AWS Data Pipeline [EOL]

Compared 18% of the time

IBM Cloud Pak for Integration vs AWS Data Pipeline [EOL]

Compared 15% of the time

MuleSoft Composer vs AWS Data Pipeline [EOL]

Compared 15% of the time

Stitch vs AWS Data Pipeline [EOL]

Compared 12% of the time

More AWS Data Pipeline [EOL] Competitors

AWS Database Migration Service vs AWS Glue

Compared 43% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 5% of the time

SSIS vs AWS Glue

Compared 4% of the time

Amazon Data Firehose vs AWS Glue

Compared 3% of the time

Palantir Foundry vs AWS Glue

Compared 3% of the time

More AWS Glue Competitors

Product Reports

Buyer's Guide

Cloud Data Integration

September 2026

Download AWS Data Pipeline [EOL] product report

Buyer's Guide

AWS Glue

September 2026

Download AWS Glue product report

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

September 2026

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