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Elastic Search vs OpenText Knowledge Discovery (IDOL) 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

Elastic Search
Ranking in Indexing and Search
1st
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
88
Ranking in other categories
Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
OpenText Knowledge Discover...
Ranking in Indexing and Search
3rd
Average Rating
8.4
Reviews Sentiment
6.3
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2026, in the Indexing and Search category, the mindshare of Elastic Search is 12.0%, down from 27.5% compared to the previous year. The mindshare of OpenText Knowledge Discovery (IDOL) is 6.3%, down from 8.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search Market Share Distribution
ProductMarket Share (%)
Elastic Search12.0%
OpenText Knowledge Discovery (IDOL)6.3%
Other81.7%
Indexing and Search
 

Featured Reviews

Vaibhav Shukla - PeerSpot reviewer
Senior Software Engineer at Agoda
Search performance has transformed large-scale intent discovery and hybrid query handling
While Elastic Search is a good product, I see areas for improvement, particularly regarding the misconception that any amount of data can simply be dumped into Elastic Search. When creating an index, careful consideration of data massaging is essential. Elastic Search stores mappings for various data types, which must remain below a certain threshold to maintain functionality. Users need to throttle the number of fields for searching to avoid overloading the system and ensure that the design of the document is efficient for the Elastic Search index. Additionally, I suggest utilizing ILM periodically throughout the year to manage data shuffling between clusters, preventing hotspots in the distribution of requests across nodes.
ERICK RAMIREZ - PeerSpot reviewer
Team Lead Solutions Architect at IMEXPERTS DO BRASIL
Scales linearly and vertically; primarily used in AI
If I am not wrong, IDOL is working to release improvements in new capabilities in the next six months. There is room for improvement in some very important capabilities in visual analytics. They have been focusing on improving the face recognition algorithm. The accuracy of object detection could be improved as well and I know they are working on that at the moment. I would like to see some machine learning capabilities added to the next release.

Quotes from Members

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

Pros

"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"ELK Elasticsearch is 100% scalable as scalability is built into the design"
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The AI-based attribute tagging is a valuable feature."
"Data indexing of historical data is the most beneficial feature of the product."
"The solution has good security features. I have been happy with the dashboards and interface."
"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."
"The forced merge and forced resonate features reduce the data size increasing reliability."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
 

Cons

"This product could be improved with additional security, and the addition of support for machine learning devices."
"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​)."
"I would like to see more integration for the solution with different platforms."
"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 upgrade experience and inflexibility with fields keeps Elastic Search from being a perfect 10."
"I would like to be able to do correlations between multiple indexes."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."
"There is room for improvement in some very important capabilities in visual analytics. They have been focusing on improving the face recognition algorithm. The accuracy of object detection could be improved as well and I know they are working on that at the moment."
 

Pricing and Cost Advice

"An X-Pack license is more affordable than Splunk."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"We are using the Community Edition because Elasticsearch's licensing model is not flexible or suitable for us. They ask for an annual subscription. We also got the development consultancy from Elasticsearch for 60 days or something like that, but they were just trying to do the same trick. That's why we didn't purchase it. We are just using the Community Edition."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"We are using the free open-sourced version of this solution."
"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
"The solution is free."
"We are using the free version and intend to upgrade."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
12%
Manufacturing Company
9%
Retailer
6%
Government
20%
Transportation Company
17%
Manufacturing Company
9%
Computer Software Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business37
Midsize Enterprise10
Large Enterprise43
No data available
 

Questions from the Community

What do you like most about ELK Elasticsearch?
Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...
What is your experience regarding pricing and costs for ELK Elasticsearch?
On the subject of pricing, Elastic Search is very cost-efficient. You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
What needs improvement with ELK Elasticsearch?
While Elastic Search is a good product, I see areas for improvement, particularly regarding the misconception that any amount of data can simply be dumped into Elastic Search. When creating an inde...
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Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
Micro Focus IDOL, HPE Autonomy IDOL, HPE IDOL
 

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.
RTVE, Krungthai Bank, Kainos, Capax Discovery
Find out what your peers are saying about Elastic Search vs. OpenText Knowledge Discovery (IDOL) and other solutions. Updated: February 2026.
881,733 professionals have used our research since 2012.