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

 

Comparison Buyer's Guide

Executive Summary

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
2
Ranking in other categories
No ranking in other categories
IBM Cloud Pak for Integration
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
API Management (27th), Cloud Data Integration (17th)
 

Featured Reviews

BR
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.
Igor Khalitov - PeerSpot reviewer
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.

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."
"Cloud Pak for Integration is definitely scalable. That is the most important criteria."
"It is a stable solution."
"Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access."
"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."
"The most valuable aspect of the Cloud Pak, in general, is the flexibility that you have to use the product."
 

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."
"Enterprise bots are needed to balance products like Kafka and Confluent."
"The initial setup is not easy."
"Its queuing and messaging features need improvement."
"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."
"The pricing can be improved."
 

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."
"It is an expensive solution."
"The solution's pricing model is very flexible."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
15%
Government
12%
Insurance Company
8%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

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What needs improvement with IBM Cloud Pak for Integration?
Enterprise bots are needed to balance products like Kafka and Confluent.
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...
What advice do you have for others considering IBM Cloud Pak for Integration?
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. Addition...
 

Overview

 

Sample Customers

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