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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
94
Ranking in other categories
Indexing and Search (1st), Search as a Service (1st), Vector Databases (3rd)
Palantir Foundry
Ranking in Cloud Data Integration
12th
Average Rating
7.8
Reviews Sentiment
7.0
Number of Reviews
18
Ranking in other categories
Data Integration (10th), 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 April 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 4.4% 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

"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."
"The most valuable features are its user-friendly interface and seamless navigation."
"Implementing the main requirements regarding my support portal​."
"I like how it allows us to connect to Kafka and get this data in a document format very easily, and Elasticsearch is very fast when you do text-based searches of documents."
"The solution is valuable for log analytics."
"It is a stable and good platform."
"The pricing and license model are clear: node-based model."
"Data indexing of historical data is the most beneficial feature of the product."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"I rate Palantir Foundry a ten out of ten."
"The solution offers very good end-to-end capabilities."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"I like the data onboarding to Palantir Foundry and ETL creation."
"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."
"It's scalable."
 

Cons

"The most significant issue I find with Elastic Search is that it gets out of sync, and this has happened in both cases where I have implemented it."
"I see that there are areas in Elastic Search that have room for improvement, such as user documentation and onboarding processes."
"The UI point of view is not very powerful because it is dependent on Kibana."
"What they need is to be more transparent about the actual setup of the cluster and the deployment process."
"The one area that can use improvement is the automapping of fields."
"The documentation regarding customization could be better."
"I know many customers who lost their data and could not recover it."
"The UI point of view is not very powerful because it is dependent on Kibana."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"There are some issues with scalability because when we are using a really large dataset, the system is rather slow."
"I rate Palantir Foundry five out of 10. I'm ambivalent."
"The workflow could be improved. Although it works rather seamlessly, the workflow is too complicated sometimes."
"Some error messages can be very cryptic."
"The frontend capabilities of Palantir Foundry could be improved."
 

Pricing and Cost Advice

"It can be expensive."
"The solution is not expensive because users have the option of choosing the managed or the subscription model."
"There is a free version, and there is also a hosted version for which you have to pay. We're currently using the free version. If things go well, we might go for the paid version."
"The version of Elastic Enterprise Search I am using is open source which is free. The pricing model should improve for the enterprise version because it is very expensive."
"The tool is an open-source product."
"The price of Elastic Enterprise is very, very competitive."
"The solution is affordable."
"To access all the features available you require both the open source license and the production license."
"Palantir Foundry is an expensive solution."
"It's expensive."
"The solution’s pricing is high."
"Palantir Foundry has different pricing models that can be negotiated."
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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
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business39
Midsize Enterprise11
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.
890,124 professionals have used our research since 2012.