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Elastic Search vs IBM Cloud Pak for Integration comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Jun 3, 2026

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

Elastic Search
Ranking in Cloud Data Integration
6th
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
100
Ranking in other categories
Indexing and Search (1st), Search as a Service (1st), Vector Databases (6th)
IBM Cloud Pak for Integration
Ranking in Cloud Data Integration
28th
Average Rating
8.6
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
API Management (36th)
 

Mindshare comparison

As of October 2026, in the Cloud Data Integration category, the mindshare of Elastic Search is 1.7%, down from 1.9% compared to the previous year. The mindshare of IBM Cloud Pak for Integration is 1.3%, down from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Elastic Search1.7%
IBM Cloud Pak for Integration1.3%
Other97.0%
Cloud Data Integration
 

Featured Reviews

reviewer2817942 - PeerSpot reviewer
Senior Software Engineer at a consultancy with 11-50 employees
Logging and vector search have transformed observability and empowered reliable ai agents
Elastic Search is not specifically being used for certain purposes. I deploy Elastic Search database on the cloud and use cloud services so that nobody can attack. However, I do not use Elastic Search to resolve attack issues. The basic main purpose of Elastic Search, as of now, I feel it can do more in the AI area. Sometime I saw that when I am developing RAG and have to generate the embeddings, which I call metadata, sometimes it tries to fail. That durability or issue handling should be improved, but apart from that, I did not find anything as of now. As per my use case, whatever I am using seems pretty good. Apart from that, some definitely improvement will be there. One improvement is that it should be faster. Whenever I am searching any logs, it takes much time. For example, if I open my log in Notepad or a similar tool, I can search the text within a second. With Elastic Search, it takes a little bit of time, ten to fifteen seconds. That can be improved. Sometimes, engineers take time to assign when I create a ticket.
Neelima Golla - PeerSpot reviewer
Senior Software Engineer at NessPRO Italy
A hybrid integration platform that applies the functionality of closed-loop AI automation
I recommend using it because, in today's context, the cloud plays a significant role. Within the same user interface, you can develop applications and manage multiple applications, making it a more user-friendly option. Moreover, you can explore various other technologies while deploying on the cloud, broadening your knowledge of cloud technologies. In my case, the transition led to my learning of Kubernetes, enabling multi-scaling and expanding my technical skills. It was a valuable experience, and I had the opportunity to learn many new things during the migration process. I can easily rate it an eight or nine 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

"We chose Elasticsearch because we could build a model in a short amount of time, allowing us to build a whole setup in one month and get 93% accuracy, with complex AI-based features built in a shorter span and with high accuracy that wasn't possible with other search enterprise vendors we used."
"A good use case is saving metadata of your systems for data cataloging. Various systems, like those opened in metadata and similar applications, use Elasticsearch to store their text data."
"The solution is stable and reliable."
"This product has notably improved the way we store and use logs, from having a more user-friendly, centralized solution (for those who just needed a quick glance, without being masters of sed and awk) to implementing various mechanisms for machine-learning from our logs, and sending alerts for anomalies."
"The flexibility and the support for diverse languages that it provides for searching the database are most valuable, and we can use different languages to query the database."
"ELK Elasticsearch is definitely a stable solution; it is the spec that surprises most of the other logging solutions in the market."
"Implementing the main requirements regarding my support portal​."
"We have many advantages from the features of Elasticsearch, and we have enough possibilities and features with Elasticsearch for our business requirements."
"In general, the solution works very, very well."
"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 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."
"It is a stable solution."
 

Cons

"I would rate technical support from Elastic Search as three out of ten. The main issue is a general sum of all factors."
"It needs email notification, similar to what Logentries has. Because of the notification issue, we moved to Logentries, as it provides a simple way to receive notification whenever a server encounters an error or unexpected conditions (which we have defined using RegEx​)."
"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"I have not explored Elastic Search at the most. Searching from vector DB is available in Elastic Search, and there is one more concept of graph searching or graph database searching. I have not explored it, but if it is not there, that would be an improvement area where Elastic Search can improve."
"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved."
"In terms of product improvement, ratio aggregation is not supported in this solution."
"The price could be better."
"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."
"What needs to be improved is the restriction that they have on the product."
"Enterprise bots are needed to balance products like Kafka and Confluent."
"The pricing can be improved."
 

Pricing and Cost Advice

"An X-Pack license is more affordable than Splunk."
"The price of Elastic Enterprise is very, very competitive."
"We are using the open-sourced version."
"The solution is less expensive than Stackdriver and Grafana."
"I rate Elastic Search's pricing an eight out of ten."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
"The solution is not expensive because users have the option of choosing the managed or the subscription model."
"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
11%
Manufacturing Company
9%
Outsourcing Company
9%
Comms Service Provider
7%
Financial Services Firm
13%
Manufacturing Company
11%
Construction Company
9%
Government
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise50
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
The pricing for Elastic Search is mainly budgeted according to the organization budget, so we take it as a yearly subscription, and that is acceptable since we do get a fair discount when we are ta...
What needs improvement with ELK Elasticsearch?
When we get the logs, it is mostly about how we edit the configurations and how we make changes according to the requirements of our organization. In these cases, the logs sometimes can be a bit in...
What is your primary use case for ELK Elasticsearch?
I am the Elastic Search admin for my organization, and we are using Elastic Search to handle the traffic to GCP. The monitoring of all the clusters and all the deployments are quite good, and compa...
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Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

Overview

 

Sample Customers

T-Mobile, Adobe, Booking.com, BMW, Telegraph Media Group, Cisco, Karbon, Deezer, NORBr, Labelbox, Fingerprint, Relativity, NHS Hospital, Met Office, Proximus, Go1, Mentat, Bluestone Analytics, Humanz, Hutch, Auchan, Sitecore, Linklaters, Socren, Infotrack, Pfizer, Engadget, Airbus, Grab, Vimeo, Ticketmaster, Asana, Twilio, Blizzard, Comcast, RWE and many others.
CVS Health Corporation
Find out what your peers are saying about Elastic Search vs. IBM Cloud Pak for Integration and other solutions. Updated: September 2026.
915,341 professionals have used our research since 2012.