Elastic Search vs Palantir Foundry comparison

Elastic and Palantir are both solutions in the Cloud Data Integration category. Elastic is ranked #5 with an average rating of 8.4, while Palantir is ranked #11 with an average rating of 8.0. Elastic holds a 1.6% mindshare in CDI, compared to Palantir’s 4.6% 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 89 Elastic Search reviews

8,328 Views
750 Comparison Views

97% willing to recommend

Palantir Foundry

Read 17 Palantir Foundry reviews

8,904 Views
1,692 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: February 2026).

Buyer's Guide

Elastic Search vs. Palantir Foundry

February 2026

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Helped 882,961 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

5th

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 February 2026, in the Cloud Data Integration category, the mindshare of Elastic Search is 1.6%, up from 1.5% compared to the previous year. The mindshare of Palantir Foundry is 4.6%, up from 3.9% 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	4.6%
Other	93.8%

Cloud Data Integration

Featured Reviews

Anurag Pal

Technical Lead at a consultancy with 10,001+ employees

Search and aggregations have transformed how I manage and visualize complex real estate data

Elastic Search consumes lots of memory. You have to provide the heap size a lot if you want the best out of it. The major problem is when a company wants to use Elastic Search but it is at a startup stage. At a startup stage, there is a lot of funds to consider. However, their use case is that they have to use a pretty significant amount of data. For that, it is very expensive. For example, if you take OLTP-based databases in the current scenario, such as ClickHouse or Iceberg, you can do it on 4GB RAM also. Elastic Search is for analytical records. You have to do the analytics on it. According to me, as far as I have seen, people will start moving from Elastic Search sooner or later. Why? Because it is expensive. Another thing is that there is an open source available for that, such as ClickHouse. Around 2014 and 2012, there was only one competitor at that time, which was Solr. But now, not only is Solr there, but you can take ClickHouse and you have Iceberg also. How are we going to compete with them? There is also a fork of Elastic Search that is OpenSearch. As far as I have seen in lots of articles I am reading, users are using it as the ELK stack for logs and analyzing logs. That is not the exact use case. It can do more than that if used correctly. But as it involves lots of cost, people are shifting from Elastic Search to other sources. When I am talking about pricing, it is not only the server pricing. It is the amount of memory it is using. The pricing is basically the heap Java, which is taking memory. That is the major problem happening here. If we have to run an MVP, a client comes to me and says, "Anurag, we need to do a proof of concept. Can we do it if I can pay a 4GB or 16GB expense?" How can I suggest to them that a minimum of 16GB is needed for Elastic Search so that your proof of concept will be proved? In that case, what I have to suggest from the beginning is to go with Cassandra or at the initial stage, go with PostgreSQL. The problem is the memory it is taking. That is the only thing.

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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.

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Quotes from Members

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

Pros

"It is a stable and good platform."

"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."

"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 most valuable feature of Elastic Enterprise Search is user behavior analysis."

"ELK Elasticsearch is 100% scalable as scalability is built into the design"

"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."

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

"From a technical point of view, there are no significant issues recalled as Elastic Search has been absolutely awesome for this use case and covers 100% of the needs."

More Elastic Search pros

"I rate Palantir Foundry a ten out of ten."

"The data lineage is great."

"The solution provides an end-to-end integrated tech stack that takes care of all utility/infrastructure topics for you."

"The solution offers very good end-to-end capabilities."

"It's scalable."

"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."

"The interface is really user-friendly."

More Palantir Foundry pros

Cons

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

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

"There are potential improvements based on our client feedback, like unifying the licensing cost structure."

"There is another solution I'm testing which has a 500 record limit when you do a search on Elastic Enterprise Search. That's the only area in which I'm not sure whether it's a limitation on our end in terms of knowledge or a technical limitation from Elastic Enterprise Search. There is another solution we are looking at that rides on Elastic Enterprise Search. And the limit is for any sort of records that you're doing or data analysis you're trying to do, you can only extract 500 records at a time. I know the open-source nature has a lot of limitations, Otherwise, Elastic Enterprise Search is a fantastic solution and I'd recommend it to anyone."

"Elasticsearch could improve by honoring Unix environmental variables and not relying only on those provided by Java (e.g. installing plugins over the Unix http proxy)."

"The real-time search functionality is not operational due to its impact on system resources."

"There were also some difficult times with parallel and point-in-time interfaces, so better documentation could help, particularly more example-driven content."

"Performance improvement could come from skipping background refresh on search idle shards (which is already being addressed in the upcoming seventh version)."

More Elastic Search cons

"The frontend capabilities of Palantir Foundry could be improved."

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

"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."

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

"The solution’s data security 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."

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

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."

"It can move from $10,000 US Dollars per year to any price based on how powerful you need the searches to be and the capacity in terms of storage and process."

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

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

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

"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 are using the free open-sourced version of this solution."

More Elastic Search pricing and cost advice

"It's expensive."

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

"Palantir Foundry is an expensive solution."

"The solution’s pricing is high."

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Top Industries

By visitors reading reviews

Financial Services Firm

12%

Computer Software Company

11%

Manufacturing Company

Retailer

Manufacturing Company

14%

Financial Services Firm

10%

Government

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	37
Midsize Enterprise	10
Large Enterprise	45

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?

On the subject of pricing, Elastic Search is very cost-efficient. You can host it on-premises, which would incur zero cost, or take it as a SaaS-based service, where the expenses remain minimal.

See all answers

What needs improvement with ELK Elasticsearch?

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 inde...

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 14% of the time

Algolia vs Elastic Search

Compared 8% of the time

Azure AI Search vs Elastic Search

Compared 6% of the time

Milvus vs Elastic Search

Compared 4% of the time

LanceDB 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

Palantir Gotham vs Palantir Foundry

Compared 4% of the time

MuleSoft Anypoint Platform vs Palantir Foundry

Compared 3% of the time

Peregrine vs Palantir Foundry

Compared 2% of the time

More Palantir Foundry Competitors

Product Reports

Buyer's Guide

Elastic Search

February 2026

Download Elastic Search product report

Buyer's Guide

Palantir Foundry

February 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

February 2026

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