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Elastic Search vs Oracle Endeca [EOL] 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
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
99
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (5th)
Oracle Endeca [EOL]
Average Rating
6.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

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.
it_user6903 - PeerSpot reviewer
Head of Engineering at CloudBearings
It’s got a good range of data visualisation components, but lacks the support for runtime complex query firing and support which OBIEE supports.
Primarily, a BI tool that enables analysis of unstructured and semi-structured data, as well as more traditional structured (measures, dimensions etc) data sets with ability to bring together loosely-related datasets and analyse them using search and lexical analysis tools. The in-memory key-value store database it uses doesn’t have the same costs around data manipulation, table joins and disk access that traditional databases have, and the column-based storage it uses is particularly suited to selecting from sets of dimension members.

Quotes from Members

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

Pros

"The tool's stability and performance are good."
"A positive feature of ELK is that it directly interacts with Elasticsearch, the UI is very nice, and performance wise it's quite good too."
"One thing I appreciate about Elastic Search is the ability to aggregate everything into one dashboard, so I can have monitoring, logs, and traces in one portal instead of having multiple different tools to do the same."
"Even compared to Splunk, Elastic Search has a good easy-to-use user interface, as even non-technical people can easily search and easily observe the logs and easily track the applications."
"I appreciate the indexing capabilities and the speed of indexing in their product, which demonstrates how quickly logs are collected and stored."
"Using real-time search functionality to support operational decisions has been helpful."
"We had many reasons to implement Elasticsearch for search term solutions. Elasticsearch products provide enterprise landscape support for different areas of the company."
"From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs."
"Primarily, a BI tool that enables analysis of unstructured and semi-structured data, as well as more traditional structured data sets with the ability to bring together loosely related datasets and analyse them using search and lexical analysis tools."
 

Cons

"It would be useful to include an assistant into Kibana for recommendations, advice, tutorials, or things that can help improve my daily work with Elastic Search."
"I would rate the stability a seven out of ten. We faced a few issues."
"Scalability of Elastic Search presents disadvantages, particularly when handling minimal or production-level data."
"I would like to see more open source tools and testing as well as a signature analysis in the solution."
"Elastic Search could benefit from a more user-friendly onboarding process for beginners."
"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."
"The GUI is the part of the program which has the most room for improvement."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"It has a good range of data visualisation components, and a web-based dashboard that appears to do a similar job to OBIEE’s interactive dashboard but lacks the support for runtime complex query firing and support which OBIEE provides through the Essbase engine."
 

Pricing and Cost Advice

"The solution is less expensive than Stackdriver and Grafana."
"We use the free version for some logs, but not extensive use."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"The tool is an open-source product."
"This product is open-source and can be used free of charge."
"The solution is affordable."
"The premium license is expensive."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Manufacturing Company
9%
Computer Software Company
8%
Construction Company
6%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise49
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
Elastic Search is easy to use in Azure cloud. Mostly, my full company uses Azure cloud, so it is easy to use. Cost-wise, my company found Elastic Search is good. Cost matters. Based on cost and use...
What needs improvement with ELK Elasticsearch?
The initial configuration could be easier; at first, the learning curve is a little high, and over time, it becomes easier. For me, the initial configuration might be improved.
What is your primary use case for ELK Elasticsearch?
We use Elastic Search for a research application based on paper study, and the primary usage is for indexing the data and then functioning in a similar way to an e-commerce search bar.
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Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
Endeca
 

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.
Virgin Media, Agilent, NHS Business Services Authority, IBFD, Valdosta State University, Ministry of Labor and Social Policy, Delphi Automotive, Riverbed
Find out what your peers are saying about Elastic, Glean, Coveo and others in Indexing and Search. Updated: June 2026.
902,456 professionals have used our research since 2012.