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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

"The AI-based attribute tagging is a valuable feature."
"It is stable."
"The most valuable feature of Elastic Enterprise Search is the Discovery option for the visualization of logs on a GPU instead of on the server."
"The product offers a powerful, cost effective solution for proprietary log management and is easy to understand and start with."
"It provides deep visibility into your cloud and distributed applications, from microservices to serverless architectures. It quickly identifies and resolves the root causes of issues, like gaining visibility into all the cloud-based and on-prem applications."
"The most valuable feature of Elastic Enterprise Search is user behavior analysis."
"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."
"The solution is valuable for log analytics."
"Encapsulates all the components without the requirement to integrate or check compatibility."
"The security is also excellent. It's highly granular, so the admins have a high degree of control, and there are many levels of security. That worked well. You won't have an EDC unless you put everything onto the platform because it is its own isolated thing."
"It's scalable."
"The predictive analytics capability within Palantir Foundry impacts financial forecasting strategies through its AIP functionality, which includes numerous pre-built models, LLMs, and data science application libraries."
"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."
"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."
"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."
"I rate Palantir Foundry a ten out of ten."
 

Cons

"We'd like to see more integration in the future, especially around service desks or other ITSM tools."
"Both the graph feature and the reporting feature are a little bit lacking. The alerting also needs to be improved."
"Machine learning on search needs improvement."
"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."
"I think the GUI part of the solution has the most room for improvement."
"The solution's integration and configuration are not easy. Not many people know exactly what to do."
"Something that could be improved is better integrations with Cortex and QRadar, for example."
"There are a lot of manual steps on the operating system. It could be simplified in the user interface."
"The frontend capabilities of Palantir Foundry could be improved."
"Difficult to receive data from external sources."
"Some error messages can be very cryptic."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"They do not have a data center in Europe, and we have lots of personally identifiable information in our dataset that needs to be hosted by a third-party data center like Amazon or Microsoft Azure."
"The data lineage was challenging. It's hard to track data from the sources as it moves through stages. Informatica EDC can easily capture and report it because it talks to the metadata. This is generated across those various staging points."
"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."
"Cost of this solution is quite high."
 

Pricing and Cost Advice

"It can be expensive."
"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."
"The premium license is expensive."
"The price of Elastic Enterprise is very, very competitive."
"The solution is not expensive because users have the option of choosing the managed or the subscription model."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"We are paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."
"ELK has been considered as an alternative to Splunk to reduce licensing costs."
"Palantir Foundry is an expensive solution."
"It's expensive."
"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.