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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
96
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

"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."
"There's lots of processing power. You can actually just add machines to get more performance if you need to. It's pretty flexible and very easy to add another log. It's not like 'oh, no, it's going to be so much extra data'. That's not a problem for the machine. It can handle it."
"Elastic is doing a fantastic job by doing the indexing, and with a couple of indexing configurations, we are able to achieve our goal even though we are maintaining a huge amount of data per day, around millions of transactions for each record."
"ELK being an open source certainly provided a platform for our organization to get involved."
"What I appreciate about Elastic Search is that the best features include the ability to search through very big documents and index and search through them really fast."
"The most valuable features of Elastic Enterprise Search are it's cloud-ready and we do a lot of infrastructure as code. By using ELK, we're able to deploy the solution as part of our ISC deployment."
"The special text processing features in this solution are very important for me."
"The initial installation and setup were straightforward."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"The virtualization tool is useful."
"I rate Palantir Foundry a ten out of ten."
"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 interface is really user-friendly."
"The interface is really user-friendly."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"The AI engine that comes with Palantir Foundry is quite interesting."
 

Cons

"It needs email notification, similar to what Logentries has. Because of the notification issue, we moved to Logentries, as it provides a simple way to receive notification whenever a server encounters an error or unexpected conditions (which we have defined using RegEx​)."
"The UI point of view is not very powerful because it is dependent on Kibana."
"I have not been using the solution for many years to know exactly the improvements needed. However, they could simplify how the YML files have to be structured properly."
"Ratio aggregation is not supported in this solution."
"The documentation regarding customization could be better."
"This product could be improved with additional security, and the addition of support for machine learning devices."
"I think Elastic Search could be improved by introducing more AI features, particularly for complex queries and aggregator functions to enhance usability and readability."
"There is a lack of technical people to develop, implement and optimize equipment operation and web queries."
"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"Difficult to receive data from external sources."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"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."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"Cost of this solution is quite high."
"If you want to create new models on specific data sets, computing that is quite costly."
"The solution’s data security could be improved."
 

Pricing and Cost Advice

"The solution is affordable."
"Elastic Search is open-source, but you need to pay for support, which is expensive."
"The solution is free."
"The tool is an open-source product."
"​The pricing and license model are clear: node-based model."
"we are using a licensed version of the product."
"To access all the features available you require both the open source license and the production license."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"It's expensive."
"Palantir Foundry is an expensive solution."
"Palantir Foundry has different pricing models that can be negotiated."
"The solution’s pricing is high."
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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 Enterprise47
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.
893,244 professionals have used our research since 2012.