Elastic Search vs Palantir Foundry comparison

Elastic and Palantir are both solutions in the Cloud Data Integration category. Elastic is ranked #6 with an average rating of 8.5, while Palantir is ranked #11 with an average rating of 7.8. Elastic holds a 1.6% mindshare in CDI, compared to Palantir’s 4.9% 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 88 Elastic Search reviews

7,984 Views
639 Comparison Views

97% willing to recommend

Palantir Foundry

Read 17 Palantir Foundry reviews

8,697 Views
1,652 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: December 2025).

Buyer's Guide

Elastic Search vs. Palantir Foundry

December 2025

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Helped 881,082 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

6th

Average Rating

8.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

Indexing and Search (1st), Search as a Service (1st), Vector Databases (2nd)

Palantir Foundry

Ranking in Cloud Data Integration

11th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Integration (12th), IT Operations Analytics (10th), Supply Chain Analytics (1st), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)

Mindshare comparison

As of January 2026, in the Cloud Data Integration category, the mindshare of Elastic Search is 1.6%, up from 1.3% compared to the previous year. The mindshare of Palantir Foundry is 4.9%, up from 3.7% 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	1.6%
Palantir Foundry	4.9%
Other	93.5%

Cloud Data Integration

Featured Reviews

Vaibhav Shukla

Senior Software Engineer at Agoda

Search performance has transformed large-scale intent discovery and hybrid query handling

While Elastic Search is a good product, I see areas for improvement, particularly regarding the misconception that any amount of data can simply be dumped into Elastic Search. When creating an index, careful consideration of data massaging is essential. Elastic Search stores mappings for various data types, which must remain below a certain threshold to maintain functionality. Users need to throttle the number of fields for searching to avoid overloading the system and ensure that the design of the document is efficient for the Elastic Search index. Additionally, I suggest utilizing ILM periodically throughout the year to manage data shuffling between clusters, preventing hotspots in the distribution of requests across nodes.

Read full review

SRINIVAS RATHOD

Architect at L&T Technology Services

Finds security and customization features impressive, although cost concerns persist

My experience with Palantir Foundry and Azure has been good. Palantir Foundry is costly, but Azure is open, which allows for easier experimentation. Being a closed product, Palantir Foundry is difficult to practice offline unless we have an enterprise edition. However, it is very secure compared to other platforms. Palantir Foundry's best features include security, built-in features, low-code, no-code platform, and ease of use. The collaborative workspaces within Palantir Foundry contribute to team efficiency and project outcomes through seamless operation. The ease of customization is particularly notable. I have worked with the data lineage feature in Palantir Foundry, which comes by default. We simply need to tick the checkbox and make necessary configuration changes within the system itself. We do not need to procure another lineage platform as Palantir Foundry has its own built-in features for data lineage, data governance, and data security. The lineage feature helps enhance our data management practices by allowing us to understand the origin of data, track all activities happening on the data, identify users and consumers, and monitor how it flows across the system. This makes it easier to generate reports based on the lineage database. 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. Using the AIP library within Palantir Foundry helps us develop quick resolutions for predictive models and analytics.

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

"The ability to aggregate log and machine data into a searchable index reduces time to identify and isolate issues for an application. Saves time in triage and incident response by eliminating manual steps to access and parse logs on separate systems, within large infrastructure footprints."

"It is stable."

"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."

"It is a stable and good platform."

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

"X-Pack provides good features, like authorization and alerts."

"Elastic Search is the perfect tool for scalability."

"Data indexing of historical data is the most beneficial feature of the product."

More Elastic Search pros

"Encapsulates all the components without the requirement to integrate or check compatibility."

"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."

"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."

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

"The data lineage is great."

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

More Palantir Foundry pros

Cons

"There are challenges with performance management and scalability."

"In Elastic Search, the improvements I would like to see require many resources."

"The documentation regarding customization could be better."

"The most significant issue I find with Elastic Search is that it gets out of sync, and this has happened in both cases where I have implemented it."

"Elastic Search should provide better guides for developers."

"Better dashboards or a better configuration system would be very good."

"We have an issue with the volume of data that we can handle."

"More AI would be beneficial. I would also appreciate more simplicity in dashboards."

More Elastic Search cons

"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."

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

"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."

"The workflow could be improved."

"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 solution could use more online documentation for new users."

"The solution’s data security could be improved."

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

More Palantir Foundry cons

Pricing and Cost Advice

"The pricing and license model are clear: node-based model."

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

"The pricing model is questionable and needs to be addressed because when you would like to have the security they charge per machine."

"The cost varies based on factors like usage volume, network load, data storage size, and service utilization. If your usage isn't too extensive, the cost will be lower."

"We are using the Community Edition because Elasticsearch's licensing model is not flexible or suitable for us. They ask for an annual subscription. We also got the development consultancy from Elasticsearch for 60 days or something like that, but they were just trying to do the same trick. That's why we didn't purchase it. We are just using the Community Edition."

"The basic license is free, but it comes with a lot of features that aren't free. With a gold license, we get active directory integration. With a platinum license, we get alerting."

"We use the free version for some logs, but not extensive use."

"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."

More Elastic Search pricing and cost advice

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

"Palantir Foundry is an expensive solution."

"It's expensive."

"The solution’s pricing is high."

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Top Industries

By visitors reading reviews

Financial Services Firm

13%

Computer Software Company

12%

Manufacturing Company

10%

Government

Manufacturing Company

14%

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	37
Midsize Enterprise	10
Large Enterprise	43

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?

Elastic Search's pricing totally depends on the server. Managed services from AWS are used, and we have worked on a self-managed Elastic Search cluster. On the AWS side, it is very expensive becaus...

See all answers

What needs improvement with ELK Elasticsearch?

To be honest, there is only one downside of Elastic Search that makes sense because we use a basic license, which is a free license. We do not have some features available because of the free licen...

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

What advice do you have for others considering Palantir Foundry?

Palantir Foundry is an excellent product for data engineering. On a scale of one to 10, I would rate Palantir Foundry a 9.

See all answers

Comparisons

Xapien vs Elastic Search

Compared 15% of the time

Algolia vs Elastic Search

Compared 9% of the time

Azure AI Search vs Elastic Search

Compared 6% of the time

Milvus vs Elastic Search

Compared 5% of the time

Solr vs Elastic Search

Compared 3% of the time

More Elastic Search Competitors

Cognizant AI & Analytics vs Palantir Foundry

Compared 8% of the time

Confluent vs Palantir Foundry

Compared 6% of the time

MuleSoft Anypoint Platform vs Palantir Foundry

Compared 3% of the time

Palantir Gotham vs Palantir Foundry

Compared 3% of the time

SAP Data Services vs Palantir Foundry

Compared 2% of the time

More Palantir Foundry Competitors

Product Reports

Buyer's Guide

Elastic Search

January 2026

Download Elastic Search product report

Buyer's Guide

Palantir Foundry

January 2026

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

December 2025

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