Elastic Search vs Palantir Foundry comparison

Elastic and Palantir are both solutions in the Cloud Data Integration category. Elastic is ranked #9 with an average rating of 8.3, while Palantir is ranked #12 with an average rating of 7.8. Elastic holds a 2.0% mindshare in CDI, compared to Palantir’s 6.2% mindshare. Additionally, 97% of Elastic users are willing to recommend the solution, compared to 88% of Palantir users who would recommend it.

Elastic Search

Read 74 Elastic Search reviews

7,566 Views
605 Comparison Views

97% willing to recommend

Palantir Foundry

Read 17 Palantir Foundry reviews

8,338 Views
1,668 Comparison Views

88% willing to recommend

Elastic Search

Palantir Foundry

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Executive SummaryUpdated on Dec 3, 2024

Elastic Search and Palantir Foundry are contenders in the data analytics and integration space. Elastic Search is favored for its affordability and flexibility due to open-source availability, while Palantir Foundry's comprehensive platform offers enhanced data integration and security capabilities.

Features: Elastic Search offers scalability, ease of integration without specific data format adjustments, and real-time analytics capabilities enhanced with Kibana. This makes it ideal for log monitoring and quick incident response. On the other hand, Palantir Foundry provides end-to-end data integration and visualization, eliminating the need for multiple tools. Its platform facilitates seamless solution deployment with a strong focus on security and advanced data handling, suited for healthcare and engineering sectors.

Room for Improvement: Elastic Search could benefit from improved security in its open-source model and more intuitive alerting features. Complexity in machine learning functionalities and index management inefficiencies are noted drawbacks. Palantir Foundry's improvements could include cost reductions and enhanced documentation. Limitations in application development and high computational costs also indicate areas for development, especially to improve accessibility for non-technical users.

Ease of Deployment and Customer Service: Elastic Search allows deployment flexibility with various configurations supported by a robust community, though direct support may be costly and slow. Versatility in deployment environments emphasizes its adaptability. Palantir Foundry focuses on seamless cloud deployments and consistent technical support, yet users report the need for faster service responses. Its higher deployment costs highlight a trade-off for smoother integration.

Pricing and ROI: Elastic Search is generally cost-effective with open-source advantages, although premium features can add up. It offers favorable ROI through cost savings in deployment and operational efficiencies. Palantir Foundry presents a higher pricing model but aims to offset this with reduced labor costs due to platform unification. While Elastic Search attracts businesses prioritizing cost-effectiveness, Foundry appeals to those valuing sophisticated data management at greater expense.

To learn more, read our detailed Elastic Search vs. Palantir Foundry Report (Updated: September 2025).

Buyer's Guide

Elastic Search vs. Palantir Foundry

September 2025

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Helped 868,759 peers since 2012

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

9th

Average Rating

8.2

Reviews Sentiment

6.6

Number of Reviews

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

7.1

Number of Reviews

Ranking in other categories

Data Integration (14th), IT Operations Analytics (9th), Supply Chain Analytics (1st), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)

Mindshare comparison

As of October 2025, in the Cloud Data Integration category, the mindshare of Elastic Search is 2.0%, up from 1.0% compared to the previous year. The mindshare of Palantir Foundry is 6.2%, up from 3.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration Market Share Distribution
Product	Market Share (%)
Elastic Search	2.0%
Palantir Foundry	6.2%
Other	91.8%

Cloud Data Integration

Featured Reviews

Louis McCoy

Director, Software Engineering at Optum Technology

Searches through billions of documents have become impressively fast and consistent

The seamless scalability is something I see as among the best features Elastic Search offers. The speed with which Elastic Search is able to search through all of the documents we place into it is quite remarkable, as we search through 65 billion documents in less than a second in most cases, on a constant consistent basis. I find configuring relevant searches within Elastic Search platform very straightforward. Elastic Search is easily scalable. The customer support for Elastic Search is quite good. I advise others looking into using Elastic Search to think about the future of your platform and where you intend it to be in five years, and based on that, which version of Elastic Search best suits the needs of your platform. Additionally, jump into the AI products first as you're in the planning phase so that as you're filling out your data, the AI products and machine learning products can enrich the data real-time early on in the process, which will save you a lot of time later. The overall performance of the platform, scalability of the platform and other additional features, especially when it comes to AI, really earn the nine.

Read full review

Rama Subba Reddy Thavva

Solution Architect at Mercedes-Benz AG

A low-code/no-code platform with a user-friendly UI

We couldn't implement or use some of the latest functionalities, like Spark. Palantir Foundry is scalable, but it is costly compared to other cloud providers. The solution is more suitable for small and medium businesses. It might be difficult for large enterprises. I rate the solution’s scalability a seven out of ten.

Read full review

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Implementing the main requirements regarding my support portal."

"The security portion of Elasticsearch is particularly beneficial, allowing me to view and analyze security alerts."

"I like how it allows us to connect to Kafka and get this data in a document format very easily. Elasticsearch is very fast when you do text-based searches of documents. That area is very good, and the search is very good."

"The solution is very good with no issues or glitches."

"The solution has great scalability."

"The most valuable feature is the out of the box Kibana."

"I value the feature that allows me to share the dashboards to different people with different levels of access."

"The most valuable feature of the solution is its utility and usefulness."

More Elastic Search pros

"Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration."

"Live video sessions enhance the available documentation and allow you to ask questions directly."

"I like the data onboarding to Palantir Foundry and ETL creation."

"The AI engine that comes with Palantir Foundry is quite interesting."

"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."

"The interface is really user-friendly."

"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."

More Palantir Foundry pros

Cons

"Elasticsearch should have simpler commands for window filtering."

"There are a lot of manual steps on the operating system. It could be simplified in the user interface."

"While integrating with tools like agents for ingesting data from sources like firewalls is valuable, I believe prioritizing improvements to the core product would be more beneficial."

"I found an issue with Elasticsearch in terms of aggregation. They are good, yet the rules written for this are not really good."

"It was not possible to use authentication three years back. You needed to buy the product's services for authentication."

"Its licensing needs to be improved. They don't offer a perpetual license. They want to know how many nodes you will be using, and they ask for an annual subscription. Otherwise, they don't give you permission to use it. Our customers are generally military or police departments or customers without connection to the internet. Therefore, this model is not suitable for us. This subscription-based model is not the best for OEM vendors. Another annoying thing about Elasticsearch is its roadmap. We are developing something, and then they say, "Okay. We have removed that feature in this release," and when we are adapting to that release, they say, "Okay. We have removed that one as well." We don't know what they will remove in the next version. They are not looking for backward compatibility from the customers' perspective. They just remove a feature and say, "Okay. We've removed this one." In terms of new features, it should have an ODBC driver so that you can search and integrate this product with existing BI tools and reporting tools. Currently, you need to go for third parties, such as CData, in order to achieve this. ODBC driver is the most important feature required. Its Community Edition does not have security features. For example, you cannot authenticate with a username and password. It should have security features. They might have put it in the latest release."

"Elastic Search needs to improve authentication. It also needs to work on the Kibana visualization dashboard."

"Something that could be improved is better integrations with Cortex and QRadar, for example."

More Elastic Search cons

"The startup pricing is high, causing concern despite being cost-effective in terms of total cost of ownership."

"The workflow could be improved."

"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."

"It requires a lot of manual work and is very time-consuming to get to a functional point."

"Difficult to receive data from external sources."

"Cost of this solution is quite high."

"If you want to create new models on specific data sets, computing that is quite costly."

"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."

More Palantir Foundry cons

Pricing and Cost Advice

"This product is open-source and can be used free of charge."

"ELK has been considered as an alternative to Splunk to reduce licensing costs."

"we are using a licensed version of the product."

"I rate Elastic Search's pricing an eight out of ten."

"The premium license is expensive."

"An X-Pack license is more affordable than Splunk."

"To access all the features available you require both the open source license and the production license."

"The solution is free."

More Elastic Search pricing and cost advice

"Palantir Foundry is an expensive solution."

"Palantir Foundry has different pricing models that can be negotiated."

"It's expensive."

"The solution’s pricing is high."

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Top Industries

By visitors reading reviews

Computer Software Company

14%

Financial Services Firm

13%

Manufacturing Company

Government

Manufacturing Company

13%

Financial Services Firm

10%

Government

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	32
Midsize Enterprise	8
Large Enterprise	36

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	5
Large Enterprise	8

Questions from the Community

What do you like most about ELK Elasticsearch?

Logsign provides us with the capability to execute multiple queries according to our requirements. The indexing is very high, making it effective for storing and retrieving logs. The real-time anal...

See all answers

What is your experience regarding pricing and costs for ELK Elasticsearch?

We used the open-source version of Elasticsearch, which was free.

See all answers

What needs improvement with ELK Elasticsearch?

Elastic Search could improve in areas such as search criteria and query processes, as search times were longer prior to implementing Elastic Search. Elastic Search has limitations for handling huge...

See all answers

What do you like most about Palantir Foundry?

Palantir Foundry is a robust platform that has really strong plugin connectors and provides features for real-time integration.

See all answers

What needs improvement with Palantir Foundry?

Apart from the pricing and offline availability issues, improvements are needed in Palantir Foundry's costing factor. Cost-wise, it is not open for everybody, and they are not exposing anything out...

See all answers

What is your primary use case for Palantir Foundry?

One of the leading European manufacturing plants uses Palantir Foundry for manufacturing interior parts of various car brands such as Honda, Hyundai, Ford, Mercedes-Benz, and BMW. This involves hig...

See all answers

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Compared 6% of the time

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Compared 4% of the time

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Compared 4% of the time

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Compared 4% of the time

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Product Reports

Buyer's Guide

Elastic Search

September 2025

Download Elastic Search product report

Buyer's Guide

Palantir Foundry

September 2025

Download Palantir Foundry product report

Also Known As

Elastic Enterprise Search, Swiftype, Elastic Cloud

No data available

Overview

Elasticsearch is a prominent open-source search and analytics engine known for its scalability, reliability, and straightforward management. It's a favored choice among enterprises for real-time data search, analysis, and visualization. Open-source Elasticsearch is free, offering a comprehensive feature set and scalability. It allows full control over deployments but requires managing and maintaining the infrastructure. On the other hand, Elastic Cloud provides a managed service with features like automated provisioning, high availability, security, and global reach.

Elasticsearch excels in handling time-sensitive data and complex search requirements across large datasets. Its scalability allows it to handle growing data volumes efficiently, maintaining high performance and fast response times. Integrated with Kibana, Elasticsearch enables powerful data visualization, providing real-time insights crucial for data-driven decision-making.

Elastic Cloud reduces operational overhead and improves scalability and performance, though it comes with associated costs. It is available on your preferred cloud provider — AWS, Azure, or Google Cloud. Customers who want to manage the software themselves, whether on public, private, or hybrid cloud, can download the Elastic Stack.

At its core, Elasticsearch is renowned for its full-text search capabilities, capable of performing complex queries and supporting features like fuzzy matching and auto-complete.

Peer reviews from various professionals highlight its strengths and weaknesses. Pros include its detection and correlation features, flexibility, cloud-readiness, extensibility, and efficient search capabilities. However, users have noted challenges like steep learning curves, data analysis limitations, and integration complexities. The platform is generally viewed as stable and scalable, with varying degrees of satisfaction regarding its usability and feature set.

In summary, Elasticsearch stands out for its high-speed search, scalability, and versatile analytics, making it a go-to solution for organizations managing large datasets. Its adaptability to different enterprise needs, robust community support, and continuous development keep it at the forefront of enterprise search and analytics solutions. However, potential users should be aware of its learning curve and the need for skilled personnel for optimization.

Elastic

Palantir Foundry is an enterprise data management platform offering comprehensive tooling for working with big data. Because it is an operating system made for modern enterprises, it is highly available and a continuously updated platform.

Palantir Foundry is a fully managed SaaS platform that spans from cloud hosting and data integration to flexible analytics, visualization, model-building, operational decision-making, and decision capture. It equips technical and non-technical users to make data-driven operational decisions.

Palantir Foundry includes tools to integrate data of any scale, format, or structure, and also has granular, flexible access controls for individual datasets. In addition, it has an open, modular architecture with multiple RESTful APIs, it has native applications for developing machine learning and artificial intelligence, it provides sophisticated data science applications for users of all technical abilities, and much more.

Palantir Foundry Features

The most valuable Palantir Foundry features include:

Security, flexibility, interoperability, easy deployment, built-in role classification, purpose-based access controls, interoperable architecture, model integration, AI modeling tools, ontology, custom workflows, team-specific applications, self-serve analytics, lineage system, operational application building, 200+ data connectors, data versioning, change management framework, sand decision orchestration, and custom dashboard and report building tools.

With Palantir Foundry You Can:

Accelerate development & operations
Collaborate globally
Save time on security
Reduce costs

Palantir Foundry Benefits

Some of the many Palantir Foundry benefits include:

Modular: Because Palantir Foundry is modular, it can integrate with existing infrastructure.
Granular governance: Robust data governance controls help ensure seamless compliance, auditability, and security.
Secure data sharing: The security infrastructure allows you to share data securely, within organizations and with chosen partners.
Rapid integration: Palantir Foundry can rapidly integrate models and data from data platforms into an operational ontology, and can also fuel existing data platforms.
Stand-alone deployment: Palantir Foundry can be deployed standalone and can provide all necessary capabilities for data connection, data integration, and model building.
Prevent lock-in: The data and model integration suites are designed to prevent lock-in, and assume that tools will be interoperating with Palantir Foundry as an organization grows.
No SQL necessary: Users do not have to use SQL queries or employ engineers to write strings in order to search petabytes of data. With Palantir Foundry, natural language is used to query data and results are returned in real-time.
Excellent data integration: Palantir Foundry provides secure, scalable, and resilient integration of all data sources.
Availability: The Palantir platform uses DNS routing, gateways and elastic load balancing to ensure availability. Dedicated accounts and virtual resources are used on a per customer basis.
Multiple metrics types: The Palantir platform provides hundreds of metrics. Some include average session length, drop-off rate, number of logins per user, number of accounts, and search speed.

Reviews from Real Users

PeerSpot users like Palantir Foundry because it has many advantages:

“It is user-friendly, good automation, and allows you to do a better job of data governance.” - Associate, Inhouse Consulting at a pharma/biotech company

“Works seamlessly with good end-to-end capabilities and the capability to scale.” - Wallace H., Sr. Director at a tech services company

Palantir

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

Buyer's Guide

Elastic Search vs. Palantir Foundry

September 2025

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