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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

"Aggregation is faster than querying directly from a database, like Postgres or Vertica, and it's much faster if I want to do aggregation, which allows me to store logs and find anomalies effectively."
"The positive impact I've seen from using Elastic Search includes replacing conventional databases and being able to store much more unstructured data."
"On the subject of pricing, Elastic Search is very cost-efficient, as you can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal."
"Elastic Search is the perfect tool for scalability."
"It gives us the possibility to store and query this data and also do this efficiently and securely and without delays."
"This is a very rich product, and it's got a very wide functionality, and a wide range of functionalities which I don't see in the other products, especially not in the cheaper ones."
"The most valuable feature of Elasticsearch is its convenience in handling unstructured data."
"Using real-time search functionality to support operational decisions has been helpful."
"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."
"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 interface is really user-friendly."
"Live video sessions enhance the available documentation and allow you to ask questions directly."
"Foundry's data visualization is fantastic."
"I rate Palantir Foundry a ten out of ten."
"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."
"The virtualization tool is useful."
 

Cons

"Enterprise scaling of what have been essentially separate, free open source software (FOSS) products has been a challenge, but the folks at Elastic have published new add-ons (X-Pack and ECE) to help large companies grow ELK to required scales."
"There are potential improvements based on our client feedback, like unifying the licensing cost structure."
"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."
"There is an index issue in which the data starts to crash as it increases."
"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."
"There are a few things that did not work for us. When doing a search in a bigger setup, with a huge amount of data where there are several things coming in, it has to be on top of the index that we search."
"Improving machine learning capabilities would be beneficial."
"I have not explored Elastic Search at the most. Searching from vector DB is available in Elastic Search, and there is one more concept of graph searching or graph database searching. I have not explored it, but if it is not there, that would be an improvement area where Elastic Search can improve."
"Some error messages can be very cryptic."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"I rate Palantir Foundry five out of 10. I'm ambivalent."
"The problem is that interaction with outside applications can be difficult with the current setup that Palantir Foundry has."
"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 frontend capabilities of Palantir Foundry could be improved."
"Difficult to receive data from external sources."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
 

Pricing and Cost Advice

"To access all the features available you require both the open source license and the production license."
"Although the ELK Elasticsearch software is open-source, we buy the hardware."
"The tool is an open-source product."
"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."
"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 solution is less expensive than Stackdriver and Grafana."
"The solution is affordable."
"It can be expensive."
"The solution’s pricing is high."
"Palantir Foundry is an expensive solution."
"It's expensive."
"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 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.
892,646 professionals have used our research since 2012.