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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

"It is easy to scale with the cluster node model.​"
"I would recommend Elastic Search to other people who want to have fast search in their applications."
"The most valuable features are its user-friendly interface and seamless navigation."
"The security portion of Elasticsearch is particularly beneficial, allowing me to view and analyze security alerts."
"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."
"The Attack Discovery feature helps to dig into incidents from where they occurred to determine how the incident originated and its source; it gives an entire path of attack propagation, showing when it started, what happened, and all events that took place to connect the entire cyber incident."
"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."
"ELK Elasticsearch is a product that I recommend."
"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

"The documentation for Elastic Search can be challenging if you're not already familiar with the platform."
"There are a few things that did not work for us. When doing a search in a bigger setup, with a huge amount of data where there are several things coming in, it has to be on top of the index that we search."
"Elastic needs to work on their Machine Learning offering because currently they have been trying to make it a black box which doesn't work for a serious user (a Data Scientist) as it doesn't give any control over the underlying algorithm."
"There are challenges with performance management and scalability."
"This is not exactly a stable solution, which is why we are considering another compatible tool, and whether we go on with Elasticsearch or change it."
"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."
"Logstash has been a challenge and needs improvements in data ingestion reconciliation."
"Improving machine learning capabilities would be beneficial."
"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 basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."
"It can be expensive."
"we are using a licensed version of the product."
"We are using the open-sourced version."
"The solution is free."
"This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
"To access all the features available you require both the open source license and the production license."
"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
9%
Computer Software Company
8%
Retailer
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.
900,747 professionals have used our research since 2012.