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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
96
Ranking in other categories
Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
OpenText Knowledge Discover...
Ranking in Indexing and Search
5th
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 May 2026, in the Indexing and Search category, the mindshare of Elastic Search is 10.9%, down from 24.9% compared to the previous year. The mindshare of OpenText Knowledge Discovery (IDOL) is 6.3%, down from 7.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search Mindshare Distribution
ProductMindshare (%)
Elastic Search10.9%
OpenText Knowledge Discovery (IDOL)6.3%
Other82.8%
Indexing and Search
 

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.
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

"The most valuable feature is the out of the box Kibana."
"Implementing the main requirements regarding my support portal​."
"Elastic Enterprise Search is a very good solution and they should keep doing good work."
"ELK being an open source certainly provided a platform for our organization to get involved."
"I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product."
"My favorite feature is always aggregations and aggregators; you do not have to do multiple queries and it is always optimized for me, and I always got the perfect results because I am using full text search with aliases and keyword search, everything I am performing it, and it always performs out of the box."
"The product offers a powerful, cost effective solution for proprietary log management and is easy to understand and start with."
"I think that Elasticsearch is a good product and cheaper than Splunk."
"Satisfaction and ability to find relevant content has increased over 50% based on our before and after survey results."
"Enterprise search success (finding what documents you're looking for) has gone up over 30% with users finding their hit on the first page of results as opposed to the 2,3,4th or giving up entirely."
"IDOL is a scalable solution: If a client needs to process more unstructured media content, they can scale IDOL both linearly and vertically, and you can scale this solution very easily."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
"Capability of processing and analysing unstructured data, like audio and video analysis."
"Speed improvements over older Fetch architecture."
 

Cons

"I think the pricing of Elastic Search is really, really expensive."
"There are some features lacking in ELK Elasticsearch."
"I think the GUI part of the solution has the most room for improvement."
"The setup is somewhat complicated due to multiple dependencies and relations with different systems."
"Kibana should be more friendly, especially when building dashboards."
"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"The metadata gets stored along with indexes and isn't queryable."
"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."
"The interface needs to be mobile friendly, which I understand is in the backlog of future improvements."
"IDOL's tech support needs improvement."
"Understanding how to optimize Lua Scripting configuration to improve performance. Lua Scripts added to a CFS configuration can cause the CFS processing to slow down, if the scripts are not scoped to only run against specific indexing jobs or database content."
"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."
"On-premise implementation and installation is very complicated."
"Technical support could improve a lot."
 

Pricing and Cost Advice

"The price of Elasticsearch is fair. It is a more expensive solution, like QRadar. The price for Elasticsearch is not much more than other solutions we have."
"We are using the open-sourced version."
"To access all the features available you require both the open source license and the production license."
"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."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"We are using the free version and intend to upgrade."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Retailer
6%
Transportation Company
16%
Government
12%
Financial Services Firm
10%
Manufacturing Company
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business39
Midsize Enterprise12
Large Enterprise47
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
When it comes to pricing, I think we had to pay AWS approximately 1,000 to 1,200 per month for the overall stack. I am not quite certain about how much Elastic Search costs specifically because I w...
What needs improvement with ELK Elasticsearch?
Elastic Search has many features, including Kibana and Logstash, which we regularly use. However, one downside in our product is cost, as it can be expensive when maintaining multiple shards and in...
What is your primary use case for ELK Elasticsearch?
As a developer, I use Elastic Search in developing one of my applications, basically integrating the back-end with Elastic Search. Our main use case for Elastic Search is for Logstash, which is a s...
Ask a question
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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: April 2026.
893,244 professionals have used our research since 2012.