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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
90
Ranking in other categories
Indexing and Search (1st), Cloud Data Integration (5th), Search as a Service (1st), Vector Databases (2nd)
Oracle Endeca [EOL]
Average Rating
6.0
Number of Reviews
1
Ranking in other categories
No ranking in other categories
 

Featured Reviews

Anurag Pal - PeerSpot reviewer
Technical Lead at a consultancy with 10,001+ employees
Search and aggregations have transformed how I manage and visualize complex real estate data
Elastic Search consumes lots of memory. You have to provide the heap size a lot if you want the best out of it. The major problem is when a company wants to use Elastic Search but it is at a startup stage. At a startup stage, there is a lot of funds to consider. However, their use case is that they have to use a pretty significant amount of data. For that, it is very expensive. For example, if you take OLTP-based databases in the current scenario, such as ClickHouse or Iceberg, you can do it on 4GB RAM also. Elastic Search is for analytical records. You have to do the analytics on it. According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive. Another thing is that there is an open source available for that, such as ClickHouse. Around 2014 and 2012, there was only one competitor at that time, which was Solr. But now, not only is Solr there, but you can take ClickHouse and you have Iceberg also. How are we going to compete with them? There is also a fork of Elastic Search that is OpenSearch. As far as I have seen in lots of articles I am reading, users are using it as the ELK stack for logs and analyzing logs. That is not the exact use case. It can do more than that if used correctly. But as it involves lots of cost, people are shifting from Elastic Search to other sources. When I am talking about pricing, it is not only the server pricing. It is the amount of memory it is using. The pricing is basically the heap Java, which is taking memory. That is the major problem happening here. If we have to run an MVP, a client comes to me and says, "Anurag, we need to do a proof of concept. Can we do it if I can pay a 4GB or 16GB expense?" How can I suggest to them that a minimum of 16GB is needed for Elastic Search so that your proof of concept will be proved? In that case, what I have to suggest from the beginning is to go with Cassandra or at the initial stage, go with PostgreSQL. The problem is the memory it is taking. That is the only thing.
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

"Search is really powerful."
"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."
"It is easy to scale with the cluster node model.​"
"The machine learning features of Elastic Search are very interesting, including the possibility to include models such as ELSER and different multilingual models that let us fine-tune our searches and use them in our search projects."
"Elastic Enterprise Search is a very good solution and they should keep doing good work."
"The stability of Elasticsearch was very high, and I would rate it a ten."
"It is a stable and good platform."
"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."
"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

"This solution is stable, but at times the stack will freeze and you have to remove and recreate the cluster."
"An improvement would be to have an interface that allows easier navigation and tracing of logs."
"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."
"Elastic Enterprise Search can improve by adding some kind of search that can be used out of the box without too much struggle with configuration. With every kind of search engine, there is some kind of special function that you need to do. A simple out-of-the-box search would be useful."
"There are challenges with performance management and scalability."
"Scalability and ROI are the areas they have to improve."
"Elastic Enterprise Search could improve the report templates."
"Could have more open source tools and testing."
"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

"To access all the features available you require both the open source license and the production license."
"we are using a licensed version of the product."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"​The pricing and license model are clear: node-based model."
"The tool is not expensive. Its licensing costs are yearly."
"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."
"The price of Elastic Enterprise is very, very competitive."
"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
Financial Services Firm
11%
Computer Software Company
10%
Manufacturing Company
9%
Retailer
7%
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business38
Midsize Enterprise10
Large Enterprise45
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?
On the subject of pricing, Elastic Search is very cost-efficient. You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.
What needs improvement with ELK Elasticsearch?
From the UI point of view, we are using most probably Kibana, and I think they can do much better than that. That is something they can fine-tune a little bit, and then it will definitely be a good...
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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, Luigi's Box, OpenText and others in Indexing and Search. Updated: March 2026.
885,286 professionals have used our research since 2012.