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Elastic Search vs Oracle Endeca [EOL] comparison

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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
100
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (6th)
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 solution has a lot of features; they have machine learning jobs they can implement, I'm not there yet, but I can use anomaly detection to see there are various processes that can find users that aren't supposed to log onto certain machines."
"This is a very rich product, and it's got a very wide functionality, and a wide range of functionalities which I don't see in the other products, especially not in the cheaper ones."
"All the quality features are there. There are about 60 to 70 reports available."
"I think that Elasticsearch is a good product and cheaper than Splunk."
"The most valuable features are its user-friendly interface and seamless navigation."
"My favorite feature is the ease of use, particularly in how you integrate the agent; I've been using it since version 7, and we're on version 9 now, and I've seen the progress from using Beats to using the agent, making it so simple today to enroll a server with the Elastic Agent."
"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."
"On the subject of pricing, Elastic Search is very cost-efficient, as you can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal."
"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

"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."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"Scalability of Elastic Search presents disadvantages, particularly when handling minimal or production-level data."
"The metadata gets stored along with indexes and isn't queryable."
"Better dashboards or a better configuration system would be very good."
"In these cases, the logs sometimes can be a bit inaccurate."
"In terms of product improvement, ratio aggregation is not supported in this solution."
"Maybe Elastic Search could improve the analytics part of the search so it can be more powerful to the user."
"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

"It can move from $10,000 US Dollars per year to any price based on how powerful you need the searches to be and the capacity in terms of storage and process."
"The price could be better."
"We are using the free version and intend to upgrade."
"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 tool is not expensive. Its licensing costs are yearly."
"We are using the free open-sourced version of this solution."
"The price of Elastic Enterprise is very, very competitive."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
11%
Manufacturing Company
9%
Outsourcing Company
7%
Computer Software Company
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business40
Midsize Enterprise12
Large Enterprise50
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
The pricing for Elastic Search is mainly budgeted according to the organization budget, so we take it as a yearly subscription, and that is acceptable since we do get a fair discount when we are ta...
What needs improvement with ELK Elasticsearch?
When we get the logs, it is mostly about how we edit the configurations and how we make changes according to the requirements of our organization. In these cases, the logs sometimes can be a bit in...
What is your primary use case for ELK Elasticsearch?
I am the Elastic Search admin for my organization, and we are using Elastic Search to handle the traffic to GCP. The monitoring of all the clusters and all the deployments are quite good, and compa...
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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: August 2026.
911,769 professionals have used our research since 2012.