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Elastic Search vs Palantir Foundry comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 3, 2024

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
Ranking in Cloud Data Integration
5th
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
95
Ranking in other categories
Indexing and Search (1st), Search as a Service (1st), Vector Databases (2nd)
Palantir Foundry
Ranking in Cloud Data Integration
10th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
18
Ranking in other categories
Data Integration (13th), IT Operations Analytics (8th), Supply Chain Analytics (1st), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of May 2026, in the Cloud Data Integration category, the mindshare of Elastic Search is 1.7%, down from 1.8% compared to the previous year. The mindshare of Palantir Foundry is 4.3%, down from 4.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Data Integration Mindshare Distribution
ProductMindshare (%)
Elastic Search1.7%
Palantir Foundry4.3%
Other94.0%
Cloud Data Integration
 

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.
BA
Associate Vice President at a insurance company with 10,001+ employees
Unified data workflows have empowered collaborative analytics and streamlined AI development
Regarding points for improvement for Palantir Foundry, I see that they are improving day by day. In the last one to two years, I have seen many improvements compared to the two years that I have worked on Palantir Foundry. There are many things that come up, but a few things are not intuitive enough. Now that we are in this AI phase, Palantir Foundry has created some wrappers around the models, allowing us to create using a no-code application, chatbots, and LLM functions. The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has. There are ways to do that, but it is not that intuitive, which is what I feel.

Quotes from Members

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

Pros

"The security portion of Elasticsearch is particularly beneficial, allowing me to view and analyze security alerts."
"The solution is valuable for log analytics."
"I have found the sort capability of Elastic very useful for allowing us to find the information we need very quickly."
"The most valuable feature is the out of the box Kibana."
"I appreciate the indexing capabilities and the speed of indexing in their product, which demonstrates how quickly logs are collected and stored."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"A nonstructured database that can manage large amounts of nonstructured data."
"If you decide to run with it, the performance and the result can be very satisfactory."
"It has been the platform for end to end data processing, manipulations, and reporting, greatly improved org's data reporting effort."
"The interface is really user-friendly."
"I rate Palantir Foundry a ten out of ten."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"This product has all the various components for getting data, transforming it and visually creating the dashboards without the need to integrate things and no need to check the compatibility."
"The AI engine that comes with Palantir Foundry is quite interesting."
"The virtualization tool is useful."
 

Cons

"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"It needs email notification, similar to what Logentries has."
"Elastic Search is stable and reliable until you build the cluster for one terabyte."
"Scalability of Elastic Search presents disadvantages, particularly when handling minimal or production-level data."
"The reports could improve."
"In Elastic Search, the improvements I would like to see require many resources."
"Pagination in Elastic Search is very slow."
"Could have more open source tools and testing."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"Cost of this solution is quite high."
"Difficult to receive data from external sources."
"The solution could use more online documentation for new users."
"The frontend capabilities of Palantir Foundry could be improved."
"I rate Palantir Foundry five out of 10. I'm ambivalent."
"The major hindrance with Palantir Foundry is that being a very closed product, the cost optimization and costing are not exposed to the end users."
"Some error messages can be very cryptic."
 

Pricing and Cost Advice

"I rate Elastic Search's pricing an eight out of ten."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"We are using the free version and intend to upgrade."
"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."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"The tool is not expensive. Its licensing costs are yearly."
"We are using the open-sourced version."
"We use the free version for some logs, but not extensive use."
"The solution’s pricing is high."
"Palantir Foundry has different pricing models that can be negotiated."
"It's expensive."
"Palantir Foundry is an expensive solution."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
9%
Manufacturing Company
9%
Retailer
6%
Manufacturing Company
13%
Financial Services Firm
9%
Government
8%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business39
Midsize Enterprise12
Large Enterprise46
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise5
Large Enterprise9
 

Questions from the Community

What is your experience regarding pricing and costs for ELK Elasticsearch?
When it comes to pricing, I think we had to pay AWS approximately 1,000 to 1,200 per month for the overall stack. I am not quite certain about how much Elastic Search costs specifically because I w...
What needs improvement with ELK Elasticsearch?
Elastic Search has many features, including Kibana and Logstash, which we regularly use. However, one downside in our product is cost, as it can be expensive when maintaining multiple shards and in...
What is your primary use case for ELK Elasticsearch?
As a developer, I use Elastic Search in developing one of my applications, basically integrating the back-end with Elastic Search. Our main use case for Elastic Search is for Logstash, which is a s...
What needs improvement with Palantir Foundry?
Regarding points for improvement for Palantir Foundry, I see that they are improving day by day. In the last one to two years, I have seen many improvements compared to the two years that I have wo...
What is your primary use case for Palantir Foundry?
There are several use cases that we are working on with Palantir Foundry. The first thing is for data model creation for all our data engineering pipelines. That is one use case. Palantir Foundry a...
What advice do you have for others considering Palantir Foundry?
The visualization part in Palantir Foundry works for me at least if I want to see how the data is structured and for an initial analysis, but I would say it is not as matured as Power BI or Tableau...
 

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud
No data available
 

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.
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about Elastic Search vs. Palantir Foundry and other solutions. Updated: April 2026.
892,868 professionals have used our research since 2012.