AWS Glue vs IBM Cloud Pak for Integration comparison

Amazon Web Services (AWS) and IBM are both solutions in the Cloud Data Integration category. Amazon Web Services (AWS) is ranked #1 with an average rating of 7.4, while IBM is ranked #16 with an average rating of 8.0. Amazon Web Services (AWS) holds a 9.8% mindshare in CDI, compared to IBM’s 1.7% mindshare. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

AWS Glue

Read 50 AWS Glue reviews

6,702 Views
4,356 Comparison Views

90% willing to recommend

IBM Cloud Pak for Integration

Read 5 IBM Cloud Pak for Integration reviews

1,260 Views
542 Comparison Views

100% willing to recommend

AWS Glue

IBM Cloud Pak for Integration

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Executive SummaryUpdated on Dec 3, 2024

AWS Glue and IBM Cloud Pak for Integration are both data integration products, with IBM Cloud Pak showing an advantage due to its extensive capabilities.

Features: AWS Glue provides strong ETL capabilities, automatic schema inference, and smooth integration with other AWS services. Meanwhile, IBM Cloud Pak for Integration offers robust support for various integration patterns, extensive connectors, and a hybrid approach suited for complex enterprise needs.

Room for Improvement: AWS Glue could improve in offering more extensive support beyond the AWS ecosystem and enhancing real-time data processing. Additionally, the user interface can be more intuitive, and it can offer more robust in-built transformation features. IBM Cloud Pak for Integration could benefit from reductions in complexity for initial setup, streamlining licensing costs, and better optimization for small to medium-sized businesses.

Ease of Deployment and Customer Service: AWS Glue provides a serverless, managed model that scales automatically, simplifying its deployment within AWS environments. IBM Cloud Pak for Integration offers flexibility with various cloud environments and on-premise options appealing to hybrid deployments. IBM is known for comprehensive support resources, which could be more advantageous than AWS Glue's support services.

Pricing and ROI: AWS Glue is competitively priced on a pay-as-you-go basis, appealing to those with budget constraints. It offers quick time-to-value. Conversely, IBM Cloud Pak for Integration, while possibly having higher initial costs, offers comprehensive enterprise-grade features that provide a higher ROI, especially in intricate integration scenarios.

To learn more, read our detailed AWS Glue vs. IBM Cloud Pak for Integration Report (Updated: December 2025).

Buyer's Guide

AWS Glue vs. IBM Cloud Pak for Integration

December 2025

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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 Glue

Ranking in Cloud Data Integration

1st

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Cloud Pak for Integration

Ranking in Cloud Data Integration

16th

Average Rating

8.6

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

API Management (28th)

Mindshare comparison

As of January 2026, in the Cloud Data Integration category, the mindshare of AWS Glue is 9.8%, down from 19.9% compared to the previous year. The mindshare of IBM Cloud Pak for Integration is 1.7%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration Market Share Distribution
Product	Market Share (%)
AWS Glue	9.8%
IBM Cloud Pak for Integration	1.7%
Other	88.5%

Cloud Data Integration

Featured Reviews

Sridivya Chillappa

application security engineer at Hyperspace IT India

Efficient data integration reduces operational time and enhances metadata management

For the initial setup with AWS Glue, I find it easy to set up the data catalog and create Glue jobs using the visual editor or the visual code. Setting permission sets via IAM rules can be a bit tricky at the start, but we ensure Glue has access to AWS S3, Redshift, and other services. Once the role is configured, it runs smoothly. For advanced configurations, connecting to VPCs and setting up connections with JDBC sources takes more time compared to my cloud experience, but overall, for someone with cloud and ETL experience, the setup is manageable and well done.

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Igor Khalitov

Owner/Full Stack Software Engineer at Maraphonic, Inc.

Manages APIs and integrates microservices with redirection feature

IBM Cloud Pak for Integration includes monitoring capabilities to track the performance and health of your integrations. You can quickly roll back to a previous version if an issue arises. Additionally, it supports incremental deployments, allowing you to shift traffic to a new version of an API gradually. For example, you can start by directing 10% of traffic to the new version while the rest continue using the legacy version. If everything works as expected, you can gradually increase the traffic to the new version over time. IBM Cloud Pak for Integration has a client base that includes numerous organizations using AI and machine learning technologies. We leverage an open-source machine learning framework and integrate it with Kafka to help create and manage various products and data retrieval processes. For companies with private data, the framework first retrieves relevant data from a GitHub database, which is then combined with the final request before being sent to a language model like GPT. This ensures that the language model uses your specific data to generate responses. Kafka plays a key role by streaming real-time data from file systems and databases like Oracle and Microsoft SQL. This data is published to Kafka topics, then vectorized and used with artificial intelligence to enhance the overall process. It's like an old-fashioned approach. The best way is to redesign it with products such as Kafka. Overall, I rate the solution an eight out of ten.

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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

"What I like best about AWS Glue is its real-time data backup feature. Last week, there was a production push, and what used to take almost ten days to send out around fifty-six thousand emails now takes only two hours."

"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."

"AWS Glue is a stable and easy-to-use solution."

"The solution is stable and reliable."

"AWS Glue is fast and managed by AWS. Hence, you don't have to worry about capacity and the performance of Glue jobs. It has integrations with other data stores of AWS. The product offers metadata management, logging, and ETL processing capabilities. It comes with a powerful feature, Glue Studio, which helps to do queries interactively within the community. It is a managed service and very secure. Another popular and mature service is S3."

"We no longer had to worry much about infrastructure management because AWS Glue is serverless, and Amazon takes care of the underlying infrastructure."

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

"AWS Glue's most valuable features are the data catalog, including crawlers and tables, and Glue Studio, which means you don't have to use custom code."

More AWS Glue pros

"The most preferable aspect would be the elimination of the command, which was a significant improvement. In the past, it was a challenge, but now we can proceed smoothly with the implementation of our policies and everything is managed through JCP. It's still among the positive aspects, and it's a valuable feature."

"Cloud Pak for Integration is definitely scalable. That is the most important criteria."

"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."

"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."

"It is a stable solution."

Cons

"The solution should offer features for streaming data in addition to batching data."

"There could be an enhanced way of managing pure metadata management or data cataloging."

"Only people who can code, either in Java or Python, can use the product freely. Those who don't know Java or Python might find using AWS Glue difficult."

"The crucial problem with AWS Glue is that it only works with AWS. It is not an agnostic tool like Pentaho. In PowerCenter, we can install the forms from Google and other vendors, but in the case of AWS Glue, we can only use AWS."

"AWS Glue should be more reliable and faster in processing. Enhancing the speed of data processing would be beneficial."

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

"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 is very difficult to learn the tool and remember the syntaxes comparatively."

More AWS Glue cons

"The initial setup is not easy."

"Setting up Cloud Pak for Integration is relatively complex. It's not as easy because it has not yet been fully integrated. You still have some products that are still not containerized, so you still have to run them on a dedicated VM."

"Enterprise bots are needed to balance products like Kafka and Confluent."

"Its queuing and messaging features need improvement."

"The pricing can be improved."

Pricing and Cost Advice

"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."

"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."

"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."

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

"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."

"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."

"It is an expensive product. I rate its pricing a nine out of ten."

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

More AWS Glue pricing and cost advice

"It is an expensive solution."

"The solution's pricing model is very flexible."

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

12%

Manufacturing Company

Insurance Company

Financial Services Firm

15%

Government

13%

Insurance Company

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	32

No data available

Questions from the Community

How do you select the right cloud ETL tool?

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

See all answers

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...

See all answers

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...

See all answers

What needs improvement with IBM Cloud Pak for Integration?

Enterprise bots are needed to balance products like Kafka and Confluent.

See all answers

What is your primary use case for IBM Cloud Pak for Integration?

It manages APIs and integrates microservices at the enterprise level. It offers a range of capabilities for handling APIs, microservices, and various integration needs. The platform supports thousa...

See all answers

What advice do you have for others considering IBM Cloud Pak for Integration?

See all answers

Comparisons

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Compared 38% of the time

SSIS vs AWS Glue

Compared 5% of the time

Palantir Foundry vs AWS Glue

Compared 5% of the time

Oracle Integration Cloud Service vs AWS Glue

Compared 4% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 4% of the time

More AWS Glue Competitors

IBM App Connect vs IBM Cloud Pak for Integration

Compared 24% of the time

MuleSoft API Manager vs IBM Cloud Pak for Integration

Compared 11% of the time

webMethods.io vs IBM Cloud Pak for Integration

Compared 9% of the time

IBM API Connect vs IBM Cloud Pak for Integration

Compared 8% of the time

Microsoft Azure API Management vs IBM Cloud Pak for Integration

Compared 6% of the time

More IBM Cloud Pak for Integration Competitors

Product Reports

Buyer's Guide

AWS Glue

January 2026

Download AWS Glue product report

Buyer's Guide

API Management

January 2026

Download IBM Cloud Pak for Integration product report

Overview

AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

AWS Glue Features

AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.
Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.
Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.
FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.
Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.
AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.
AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.
AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.
Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.
AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

AWS Glue Benefits

AWS Glue offers a wide range of benefits for its users. These benefits include:

Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.
The solution is serverless, which allows for a lower total cost of ownership.
AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.
The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.
AWS Glue does not require additional payment for managing and enforcing schemas for data streams.
The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

Reviews from Real Users

Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

Amazon Web Services (AWS)

IBM Cloud Pak for Integration gives you complete, flexible integration using capabilities you need to move at today's speed of business, including the tools to help you achieve your application modernization goals as part of your journey to the cloud.

IBM

Sample Customers

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

CVS Health Corporation

Buyer's Guide

AWS Glue vs. IBM Cloud Pak for Integration

December 2025

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