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Lucene 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

Lucene
Ranking in Indexing and Search
9th
Average Rating
8.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
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 March 2026, in the Indexing and Search category, the mindshare of Lucene is 5.4%, up from 5.0% compared to the previous year. The mindshare of OpenText Knowledge Discovery (IDOL) is 6.1%, down from 7.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search Mindshare Distribution
ProductMindshare (%)
OpenText Knowledge Discovery (IDOL)6.1%
Lucene5.4%
Other88.5%
Indexing and Search
 

Featured Reviews

it_user1158 - PeerSpot reviewer
Developer at a tech company with 51-200 employees
One of the best open source date indexing tools available, with support for various popular file formats like PDF, HTML, etc.
- For Java users, there is a performance penalty due to the well known fact that JVM(Java Virtual Memory) is a memory hogger. Scalability is an issue as well. - If you have a requirement of adding custom algorithms for indexing data, you might face a little difficulty, as there is not much information available either in Lucene forums or mailing lists. Though community support is excellent for Java users, for other area specific Programming Platforms like Perl, and Delphi, it is a bit difficult to get solutions for your problems, as the tool is still not that stable in these platforms and is still in the incubation phase.
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

"A very good product for indexing huge data with a very fast response time for search queries."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
"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."
"Speed improvements over older Fetch architecture."
"Capability of processing and analysing unstructured data, like audio and video analysis."
 

Cons

"If you have a requirement of adding custom algorithms for indexing data, you might face a little difficulty, as there is not much information available either in Lucene forums or mailing lists."
"The interface needs to be mobile friendly, which I understand is in the backlog of future improvements."
"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."
"Technical support could improve a lot."
"On-premise implementation and installation is very complicated."
"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."
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Top Industries

By visitors reading reviews
No data available
Transportation Company
18%
Government
16%
Manufacturing Company
10%
Computer Software Company
8%
 

Company Size

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

Also Known As

No data available
Micro Focus IDOL, HPE Autonomy IDOL, HPE IDOL
 

Overview

 

Sample Customers

Bloomberg, Salesforce, Bank of America, AT&T, SAP, JP Morgan Chase, Capital One, DirecTV, Boeing, Monsanto, Warner Bros, The Walt Disney Company, Goldman Sachs, Fiat Chrysler Automobiles, BlackRock
RTVE, Krungthai Bank, Kainos, Capax Discovery
Find out what your peers are saying about Elastic, Luigi's Box, OpenText and others in Indexing and Search. Updated: February 2026.
884,933 professionals have used our research since 2012.