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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

"Elastic Search is very user-friendly, and we can easily integrate it with third-party models and other AWS S3 buckets."
"The product is scalable with good performance."
"Elastic Enterprise Search is scalable. On a scale of one to 10, with one being not scalable and 10 being very scalable, I give Elastic Enterprise Search a 10."
"The products comes with REST APIs."
"We can easily collect all the data and view historical trends using the product. We can view the applications and identify the issues effectively."
"ELK being an open source certainly provided a platform for our organization to get involved."
"It gives us the possibility to store and query this data and also do this efficiently and securely and without delays."
"This has improved our organization because we articulated Kubernetes, Docker, and GitHub with amazing simplicity in the scaling up of our service."
"The interface is really user-friendly."
"I like the data onboarding to Palantir Foundry and ETL creation."
"The data lineage is great."
"The solution offers very good end-to-end capabilities."
"It has been the platform for end to end data processing, manipulations, and reporting, greatly improved org's data reporting effort."
"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."
"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"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."
 

Cons

"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search."
"There is an index issue in which the data starts to crash as it increases."
"I would like to see more integration for the solution with different platforms."
"I don't see improvements at the moment. The current setup is working well for me, and I'm satisfied with it. Integrating with different platforms is also fine, and I'm not recommending any changes or enhancements right now."
"The real-time search functionality is not operational due to its impact on system resources."
"The setup is somewhat complicated due to multiple dependencies and relations with different systems."
"Scalability of Elastic Search presents disadvantages, particularly when handling minimal or production-level data."
"There is a maximum of 10,000 entries, so the limitation means that if I wanted to analyze certain IP addresses more than 10,000 times, I wouldn't be able to dump or print that information."
"The solution could use more online documentation for new users."
"Difficult to receive data from external sources."
"The workflow could be improved. Although it works rather seamlessly, the workflow is too complicated sometimes."
"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."
"It requires a lot of manual work and is very time-consuming to get to a functional point."
"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 startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."
"I rate Palantir Foundry five out of 10. I'm ambivalent."
 

Pricing and Cost Advice

"Elastic Search is open-source, but you need to pay for support, which is expensive."
"The tool is an open-source product."
"The price of Elastic Enterprise is very, very competitive."
"This is a free, open source software (FOSS) tool, which means no cost on the front-end. There are no free lunches in this world though. Technical skill to implement and support are costly on the back-end with ELK, whether you train/hire internally or go for premium services from Elastic."
"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 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."
"Palantir Foundry is an expensive solution."
"The solution’s pricing is high."
"Palantir Foundry has different pricing models that can be negotiated."
"It's expensive."
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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 Enterprise13
 

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.
893,311 professionals have used our research since 2012.