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 #11 with an average rating of 7.8. Elastic holds a 2.1% mindshare in CDI, compared to Palantir’s 5.6% 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 71 Elastic Search reviews

6,694 Views
469 Comparison Views

97% willing to recommend

Palantir Foundry

Read 17 Palantir Foundry reviews

8,962 Views
1,792 Comparison Views

88% willing to recommend

Elastic Search

Palantir Foundry

Comparison Buyer's Guide

Download the report

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: June 2025).

Buyer's Guide

Elastic Search vs. Palantir Foundry

June 2025

Download the complete report

Helped 861,170 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

6.8

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

11th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

Data Integration (14th), 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 July 2025, in the Cloud Data Integration category, the mindshare of Elastic Search is 2.1%, up from 0.6% compared to the previous year. The mindshare of Palantir Foundry is 5.6%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration

Featured Reviews

Anand_Kumar

Enterprise Architect at DXC Technology

Captures data from all other sources and becomes a MOM aka monitoring of monitors

Scalability and ROI are the areas they have to improve. Their license terms are based on the number of cores. If you increase the number of cores, it becomes very difficult to manage at a large scale. For example, if I have a $3 million project, I won't sell it because if we're dealing with a 10 TB or 50 TB system, there are a lot of systems and applications to monitor, and I have to make an MOM (Mean of Max) for everything. This is because of the cost impact. Also, when you have horizontal scaling, it's like a multi-story building with only one elevator. You have to run around, and it's not efficient. Even the smallest task becomes difficult. That's the problem with horizontal scaling. They need to improve this because if they increase the cores and adjust the licensing accordingly, it would make more sense.

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

"It is highly valuable because of its simplicity in maintenance, where most tasks are handled for you, and it offers a plethora of built-in features."

"Using real-time search functionality to support operational decisions has been helpful."

"You have dashboards, it is visual, there are maps, you can create canvases. It's more visual than anything that I've ever used."

"The search speed is most valuable and important."

"Elastic Search is very quick when handling a large volume of data."

"The stability of Elasticsearch was very high, and I would rate it a ten."

"The initial installation and setup were straightforward."

"I really like the visualization that you can do within it. That's really handy. Product-wise, it is a very good and stable product."

More Elastic Search pros

"Great features available in one tool."

"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."

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

"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."

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

"The data lineage is great."

"The interface is really user-friendly."

"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

"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."

"Improving machine learning capabilities would be beneficial."

"The price could be better. Kibana has some limitations in terms of the tablet to view event logs. I also have a high volume of data. On the initialization part, if you chose Kibana, you'll have some limitations. Kibana was primarily proposed as a log data reviewer to build applications to the viewer log data using Kibana. Then it became a virtualization tool, but it still has limitations from a developer's point of view."

"We'd like to see more integration in the future, especially around service desks or other ITSM tools."

"It should be easier to use. It has been getting better because many functions are pre-defined, but it still needs improvement."

"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."

"The solution has quite a steep learning curve. The usability and general user-friendliness could be improved. However, that is kind of typical with products that have a lot of flexibility, or a lot of capabilities. Sometimes having more choices makes things more complex. It makes it difficult to configure it, though. It's kind of a bitter pill that you have to swallow in the beginning and you really have to get through it."

"Ratio aggregation is not supported in this solution."

More Elastic Search cons

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

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

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

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

"The solution's visualization and analysis could be improved."

"It would be helpful to build applications based on Azure functions or web apps in Palantir Foundry."

"Cost of this solution is quite high."

"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."

More Palantir Foundry cons

Pricing and Cost Advice

"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 paying $1,500 a month to use the solution. If you want to have endpoint protection you need to pay more."

"The solution is free."

"The tool is not expensive. Its licensing costs are yearly."

"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 solution is not expensive because users have the option of choosing the managed or the subscription model."

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

"Elastic Search is open-source, but you need to pay for support, which is expensive."

More Elastic Search pricing and cost advice

"Palantir Foundry is an expensive solution."

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

"The solution’s pricing is high."

"It's expensive."

See which vendors are best for you

Use our free recommendation engine to learn which Cloud Data Integration solutions are best for your needs.

See recommendations

861,170 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

16%

Financial Services Firm

14%

Manufacturing Company

Government

Manufacturing Company

14%

Financial Services Firm

10%

Computer Software Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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?

It would be useful if a feature for renaming indices could be added without affecting the performance of other features. However, overall, the consistency and stability of Elasticsearch are already...

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

Comparisons

Milvus vs Elastic Search

Compared 11% of the time

Algolia vs Elastic Search

Compared 9% of the time

Faiss vs Elastic Search

Compared 7% of the time

Azure Search vs Elastic Search

Compared 6% of the time

Qdrant vs Elastic Search

Compared 4% of the time

More Elastic Search Competitors

Azure Data Factory vs Palantir Foundry

Compared 7% of the time

Palantir Gotham vs Palantir Foundry

Compared 5% of the time

Aera vs Palantir Foundry

Compared 4% of the time

SAP Data Services vs Palantir Foundry

Compared 4% of the time

Informatica PowerCenter vs Palantir Foundry

Compared 3% of the time

More Palantir Foundry Competitors

Product Reports

Buyer's Guide

Elastic Search

July 2025

Download Elastic Search product report

Buyer's Guide

Palantir Foundry

June 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

June 2025

Free Report: Elastic Search vs. Palantir Foundry

Find out what your peers are saying about Elastic Search vs. Palantir Foundry and other solutions. Updated: June 2025.

DOWNLOAD NOW

861,170 professionals have used our research since 2012.

See our Elastic Search vs. Palantir Foundry report.

See our list of best Cloud Data Integration vendors.

We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.