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Elastic Search vs OpenText IDOL comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Elastic Search
Ranking in Indexing and Search
1st
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
65
Ranking in other categories
Cloud Data Integration (12th), Search as a Service (1st), Vector Databases (1st)
OpenText IDOL
Ranking in Indexing and Search
4th
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 December 2024, in the Indexing and Search category, the mindshare of Elastic Search is 28.1%, up from 25.1% compared to the previous year. The mindshare of OpenText IDOL is 8.8%, up from 7.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Indexing and Search
 

Featured Reviews

Saurav Kumar - PeerSpot reviewer
Provides us with the capability to execute multiple queries according to our requirements
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 analytics with Elastic benefits us due to the huge traffic volume in our organization, which reaches up to 60,000 requests per second. With logs of approximately 25 GB per day, manually analyzing traffic behavior, payloads, headers, user agents, and other details is impractical.
ERICK RAMIREZ - PeerSpot reviewer
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 for us is the analytics that we can configure and view using Kibana."
"Data indexing of historical data is the most beneficial feature of the product."
"The most valuable features are the detection and correlation features."
"The most valuable feature of Elastic Enterprise Search is the Discovery option for the visualization of logs on a GPU instead of on the server."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"The initial setup is fairly simple."
"Using real-time search functionality to support operational decisions has been helpful."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"IDOL has several important visual analytics, like face recognition and object detection and recognition."
 

Cons

"Elastic Enterprise Search's tech support is good but it could be improved."
"Could have more open source tools and testing."
"The GUI is the part of the program which has the most room for improvement."
"The pricing of this product needs to be more clear because I cannot understand it when I review the website."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"I would like to be able to do correlations between multiple indexes."
"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."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"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

"we are using a licensed version of the product."
"We are using the open-sourced version."
"The price of Elastic Enterprise is very, very competitive."
"​The pricing and license model are clear: node-based model."
"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."
"The price could be better."
"The solution is free."
"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."
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Top Industries

By visitors reading reviews
Computer Software Company
19%
Financial Services Firm
15%
Manufacturing Company
8%
Government
7%
Transportation Company
17%
Government
13%
Manufacturing Company
11%
Financial Services Firm
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
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?
I am not directly involved with pricing or setup costs. While I know a portion is open-source, a paid version might be necessary.
What needs improvement with ELK Elasticsearch?
An improvement would be to have an interface that allows easier navigation and tracing of logs. The current system requires manually inputting dates to verify alerts. A visual timeline that pinpoin...
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Comparisons

No data available
 

Also Known As

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

Learn More

 

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.
Bank Simpanan Nasional, Felco
Find out what your peers are saying about Elastic Search vs. OpenText IDOL and other solutions. Updated: December 2024.
824,053 professionals have used our research since 2012.