Palantir Foundry vs Teradata comparison

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Palantir Foundry

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Executive SummaryUpdated on Jan 12, 2025

Teradata and Palantir Foundry compete in the data management and analytics market. Teradata shows strength in handling complex analytical functions due to its advanced parallel architecture, while Palantir Foundry stands out for its superior data integration and visualization features.

Features: Teradata's key features include strong parallel processing capabilities, advanced partitioning, and workload management, making it ideal for massive data operations and complex queries. Palantir Foundry excels in data integration across platforms, real-time capabilities, and provides robust tools for data transformation and pipeline management.

Room for Improvement: For Teradata, there is room for improvement in cost management, scalability, and cloud adoption, along with better handling of unstructured data. Its pricing and licensing are often viewed as expensive. Palantir Foundry could benefit from more intuitive technical support and documentation, enhanced data exporting capabilities, and more comprehensive Python support. The interface and cost are also areas of concern.

Ease of Deployment and Customer Service: Teradata offers versatility with on-premises and hybrid cloud environments, providing flexibility and generally high-rated technical support, although response times can improve. Palantir Foundry focuses on public cloud deployment, offering a centralized integration system, and users appreciate its cohesive environment but desire faster support resolutions.

Pricing and ROI: Teradata is acknowledged as a premium product with high costs, serving large projects well with a strong ROI despite being a barrier for smaller businesses. Palantir Foundry also has a high price, justified by its comprehensive features and reduced development needs, with users noting significant ROI. Cost considerations are significant for both, with Teradata noted for consistent performance benefits.

To learn more, read our detailed Palantir Foundry vs. Teradata Report (Updated: January 2025).

Palantir Foundry vs. Teradata

January 2025

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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

Palantir Foundry

Ranking in Data Integration

19th

Average Rating

7.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

IT Operations Analytics (9th), Supply Chain Analytics (1st), Cloud Data Integration (14th), Data Migration Appliances (4th), Data Management Platforms (DMP) (2nd), Data and Analytics Service Providers (1st)

Teradata

Ranking in Data Integration

16th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (4th), Backup and Recovery (20th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Mindshare comparison

As of February 2025, in the Data Integration category, the mindshare of Palantir Foundry is 2.5%, down from 2.6% compared to the previous year. The mindshare of Teradata is 0.8%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

Featured Reviews

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.

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SurjitChoudhury

Data engineer at Cocos pt

Offers seamless integration capabilities and performance optimization features, including extensive indexing and advanced tuning capabilities

We created and constructed the warehouse. We used multiple loading processes like MultiLoad, FastLoad, and Teradata Pump. But those are loading processes, and Teradata is a powerful tool because if we consider older technologies, its architecture with nodes, virtual processes, and nodes is a unique concept. Later, other technologies like Informatica also adopted the concept of nodes from Informatica PowerCenter version 7.x. Previously, it was a client-server architecture, but later, it changed to the nodes concept. Like, we can have the database available 24/7, 365 days. If one node fails, other nodes can take care of it. Informatica adopted all those concepts when it changed its architecture. Even Oracle databases have since adapted their architecture to them. However, this particular Teradata company initially started with its own different type of architecture, which major companies later adopted. It has grown now, but initially, whatever query we sent it would be mapped into a particular component. After that, it goes to the virtual processor and down to the disk, where the actual physical data is loaded. So, in between, there's a map, which acts like a data dictionary. It also holds information about each piece of data, where it's loaded, and on which particular virtual processor or node the data resides. Because Teradata comes with a four-node architecture, or however many nodes we choose, the cost is determined by that initially. So, what type of data does each and every node hold? It's a shared-no architecture. So, whatever task is given to a virtual processor it will be processed. If there's a failure, then it will be taken care of by another virtual processor. Moreover, this solution has impacted the query time and data performance. In Teradata, there's a lot of joining, partitioning, and indexing of records. There are primary and secondary indexes, hash indexing, and other indexing processes. To improve query performance, we first analyze the query and tune it. If a join needs a secondary index, which plays a major role in filtering records, we might reconstruct that particular table with the secondary index. This tuning involves partitioning and indexing. We use these tools and technologies to fine-tune performance. When it comes to integration, tools like Informatica seamlessly connect with Teradata. We ensure the Teradata database is configured correctly in Informatica, including the proper hostname and properties for the load process. We didn't find any major complexity or issues with integration. But, these technologies are quite old now. With newer big data technologies, we've worked with a four-layer architecture, pulling data from Hadoop Lake to Teradata. We configure Teradata with the appropriate hostname and credentials, and use BTEQ queries to load data. Previously, we converted the data warehouse to a CLD model as per Teradata's standardized procedures, moving from an ETL to an EMT process. This allowed us to perform gap analysis on missing entities based on the model and retrieve them from the source system again. We found Teradata integration straightforward and compatible with other tools.

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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

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

"The data lineage is great."

"It's scalable."

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

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

"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."

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

More Palantir Foundry pros

"It is a solid database a lot of different tools to move data."

"Things have started moving faster in my company, such as data retrieval happens more quickly."

"It has given our business the ability to gain insights into the data and create data labs for analysis and PoCs."

"The cloud is ten times better than physical hardware; it is more cost-effective and the upgrade process is ten times easier."

"Teradata is a great, industry-leading data warehousing product that has MPP architecture."

"The performance is great, we are able to query our data in one operation."

"Teradata effectively uses parallelism to the granular level, performing better than other databases."

"The ability to handle machine data parallel processing is the most valuable feature of Teradata."

More Teradata pros

Cons

"Some error messages can be very cryptic."

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

"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."

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

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

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

More Palantir Foundry cons

"The scalability could be better. The on-premises solution is always more complicated to scale."

"The initial setup was complex as we had to rewrite a lot of the code."

"I would like more security and speed."

"Teradata needs to expand the kind of training that's available to customers. Teradata only offers training directly and doesn't delegate to any third-party companies. As a result, it's harder to find people trained on Teradata in our market relative to Oracle."

"Teradata needs to pay attention to the cloud-based solution to make sure it runs smoothly."

"The capability to implement it with comparable performance across various private cloud environments, ensuring adaptability to different infrastructure setups would be beneficial."

"The solution needs improvement in its stability, support and pricing."

"The tool's flexibility and capacity for expansion are areas of concern where improvements are required."

More Teradata cons

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."

"It is still a very expensive solution. While I very much like the pure technological supremacy of the software itself, I believe Teradata as a company needs to become more affordable. They are already losing the market to more flexible or cheaper competitors."

"Users have to pay a yearly licensing fee for Teradata IntelliFlex, which is very expensive."

"In the past, it turned out that other solutions, in order to provide the full range of abilities that the Teradata platform provides plus the migration costs, would end up costing more than Teradata does."

"It comes at a notably high cost for what it offers."

"Make sure you have the in-house skills to design and support the solution, as relying on external sources is extremely costly and tends to lock you into specific platforms, tools, and paradigms."

"The cost is substantial, totaling around $1.2 million, solely dedicated to upgrading the hardware."

"Teradata pricing is fine, and it's competitive with all the legacy models. On a scale of one to five, with one being the worst and five being the best, I'm giving Teradata a three, because it can be a little expensive, when compared to other solutions."

"I would advise others to look into migration and setup as a fixed price and incorporate a SaaS option for other Teradata services."

More Teradata pricing and cost advice

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Comparison Review

it_user232068

Senior Data Architect at a pharma/biotech company with 1,001-5,000 employees

Aug 5, 2015

Netezza vs. Teradata

Original published at https://www.linkedin.com/pulse/should-i-choose-net Two leading Massively Parallel Processing (MPP) architectures for Data Warehousing (DW) are IBM PureData System for Analytics (formerly Netezza) and Teradata. I thought talking about the similarities and differences…

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Top Industries

By visitors reading reviews

Manufacturing Company

14%

Financial Services Firm

11%

Computer Software Company

10%

Government

Financial Services Firm

27%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

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.

What needs improvement with Palantir Foundry?

The solution’s data security could be improved. We cannot use many Python packages with the solution. We were able to use only a few compatible Python packages.

What is your primary use case for Palantir Foundry?

Our use cases are mostly related to data analytics. We are building some dashboards and ETL pipelines on the Palantir side. Palantir Foundry is a low-code/no-code platform with a user-friendly UI. ...

Comparing Teradata and Oracle Database, which product do you think is better and why?

I have spoken to my colleagues about this comparison and in our collective opinion, the reason why some people may declare Teradata better than Oracle is the pricing. Both solutions are quite simi...

Which companies use Teradata and who is it most suitable for?

Before my organization implemented this solution, we researched which big brands were using Teradata, so we knew if it would be compatible with our field. According to the product's site, the comp...

Is Teradata a difficult solution to work with?

Teradata is not a difficult product to work with, especially since they offer you technical support at all levels if you just ask. There are some features that may cause difficulties - for example,...

Azure Data Factory vs Palantir Foundry

Comparisons

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Compared 6% of the time

SAP Data Services vs Palantir Foundry

Compared 5% of the time

Domo vs Palantir Foundry

Compared 4% of the time

AWS Glue vs Palantir Foundry

Compared 4% of the time

More Palantir Foundry Competitors

Oracle Exadata vs Teradata

Compared 14% of the time

SQL Server vs Teradata

Compared 11% of the time

MySQL vs Teradata

Compared 8% of the time

Snowflake vs Teradata

Compared 7% of the time

IBM Db2 Database vs Teradata

Compared 6% of the time

More Teradata Competitors

Product Reports

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Palantir Foundry

February 2025

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February 2025

Also Known As

No data available

IntelliFlex, Aster Data Map Reduce, , QueryGrid, Customer Interaction Manager, Digital Marketing Center, Data Mover, Data Stream Architecture

Overview

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

Teradata is a scalable data analytics platform designed to meet enterprise demands for large-scale data management and processing, focusing on performance, scalability, and security for complex query executions.

As a leading data warehousing solution, Teradata integrates advanced analytics enabling organizations to derive insights from massive datasets. It supports high-volume data workloads with its architecture optimized for analytical queries. Users benefit from its robust scalability, allowing seamless expansion as data grows. Teradata's SQL engine is compatible with a wide range of data types, ensuring flexibility in data analysis. With advanced security measures, it protects sensitive data across various environments, providing peace of mind to users handling critical information.

What are the most important features of Teradata?

Linear Scalability: Easily expands data processing capabilities to handle increasing data loads without performance degradation.
Advanced Analytics: Supports complex analytical operations integrating machine learning and AI for predictive insights.
SQL Compatibility: Offers a comprehensive SQL interface that supports complex queries across diverse data types.
Data Security: Implements rigorous security protocols to protect data integrity and confidentiality.

What benefits and ROI should users look for?

Improved Decision-Making: Derive actionable insights quickly for strategic business decisions.
Cost Efficiency: Optimized resource usage reduces operational costs associated with data processing.
Increased Productivity: Streamlined data operations save time, allowing teams to focus on analysis.
Enhanced Scalability: Seamless growth without significant additional investment as data volumes increase.

Teradata is widely used in industries like finance, telecommunications, and healthcare, where data-driven decisions are critical. Companies leverage its robust analytics capabilities to enhance customer experiences, streamline operations, and ensure compliance with regulatory requirements. In these sectors, quick access to data insights can significantly impact competitive advantage.

Sample Customers

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense

Netflix