Palantir Foundry vs Teradata comparison

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Palantir Foundry

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Executive SummaryUpdated on Oct 6, 2024

Teradata and Palantir Foundry compete in data management and analytics. Palantir Foundry appears to have the upper hand due to its comprehensive features, despite Teradata's advantage in pricing and support.

Features: Teradata is valued for its scalable data warehousing capabilities, integrated analytics tools, and efficient handling of complex queries. Palantir Foundry offers an advanced analytics platform, seamless enterprise integration, and powerful data visualization tools. Both products differ in approach, with Teradata focusing on traditional data warehousing, while Palantir Foundry emphasizes transformative analytics.

Room for Improvement: Teradata users suggest enhancing cloud integration, improving system flexibility, and streamlining data migration. Palantir Foundry users express a need for better documentation, enhanced training resources, and a reduced learning curve for new users, which could improve onboarding.

Ease of Deployment and Customer Service: Teradata has reliable deployment options and effective customer service, suitable for large enterprises. Palantir Foundry provides flexible deployment backed by responsive support, though its initial setup can be complex. The two differ mainly in Teradata's structured deployment versus Palantir Foundry's flexibility.

Pricing and ROI: Teradata is seen as cost-effective with pricing models that provide good ROI through efficient data management. Palantir Foundry, although costlier, is justified by users due to its advanced analytical capabilities offering strong ROI. Teradata is more affordable, whereas Palantir Foundry is perceived as valuable.

To learn more, read our detailed Palantir Foundry vs. Teradata Report (Updated: November 2024).

Palantir Foundry vs. Teradata

November 2024

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Categories and Ranking

Palantir Foundry

Ranking in Data Integration

12th

Average Rating

7.6

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

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

Teradata

Ranking in Data Integration

18th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Customer Experience Management (5th), Backup and Recovery (19th), Relational Databases Tools (7th), Data Warehouse (3rd), BI (Business Intelligence) Tools (10th), Marketing Management (6th), Cloud Data Warehouse (6th)

Featured Reviews

Manilal Kasera

Senior Software Engineer at Tiger Analytics

Transparent with good reliability and good data visibility

The initial setup had a medium level of difficulty. If we go through the documentation, we can learn about what to do. In Palantir, they had a section called Academy, and that Academy was quite useful. If you go through that as a new user, it makes the process easier as you learn what to do. Initially, we didn't have many sources that would help us learn things, so we struggled a bit. In contrast, with Azure and Amazon Cloud, you have many sources from where you would be easily able to learn. You could just Google what you needed with them, as there's so much available documentation online. What was easy was the fact that everything was in one place. With AWS Cloud, there are many applications to support. You can use Glue or Athena, and you have all these other applications. However, with Palantir, everything is easy due to the fact that it is centralized. It's drag and drop and everything is very transparent.

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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

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

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

"The virtualization tool is useful."

"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 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."

"Great features available in one tool."

"The ease of use is my favorite feature. We're able to build different models and projects or combine different projects to build one use case."

More Palantir Foundry pros

"The product is reliable."

"It's the same as your visual database. I like the fast load feature for data, the BTQ solution is very good, and storage procedures are very fast."

"It is quick, secure, and has less hassles because we don't have to involve our networking team, infrastructure, etc. It is very easy to deploy and make market ready."

"Parallel processing features have helped to easily dump any size of data and retrieve data with great performance."

"The most valuable feature of Teradata is the quick processing of large data."

"It has reduced a lot of reworking on maintaining indexes, partitions, etc."

"The solution's banking model, called FSLDM (Financial Services Logical Data Model), is sophisticated and good."

"Teradata can be easily used in ETL mode transformations, so there is no need for expensive and inconvenient ETL tools"

More Teradata pros

Cons

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

"Cost of this solution is quite high."

"The workflow could be improved."

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

"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."

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

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

"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

"The cost of Teradata Cloud Data Warehouse has room for improvement."

"Needs compatibility with more Big Data platforms."

"The SQL Assistant is very basic. This tool can be improved for usability."

"Teradata is somewhat late in adopting cloud technology."

"Query language and its functionality are rather limited, compared to Oracle or even SQL Server. However, it is possible to perform any kind of logic in it (though some workarounds may be required)."

"Their level of technical support is adequate. It could be better."

"The only issue our company has with Teradata IntelliFlex is that it is not cost-effective because of the way the product has been designed."

"There is some improvement required on OLTP level and some analytical function is missing."

More Teradata cons

Pricing and Cost Advice

"The solution’s pricing is high."

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

"It's expensive."

"Palantir Foundry is an expensive solution."

"Teradata's licensing is on the expensive side."

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

"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."

"The price of Teradata is expensive. However, what they deliver they are outstanding. If you're looking for an inexpensive solution to run a database, this isn't your tool. It's the Ferrari of databases for data warehousing."

"We are looking for a more flexible cost model for the next version that we use, whether it be cloud or on-premise."

"The price needs to be more competitive as Hadoop, Redshift, Snowflake, etc are constantly making way into EDW space."

"The price of Teradata could be less expensive."

"Teradata is a very expensive solution."

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

26%

Computer Software Company

11%

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

Compared 13% of the time

Palantir Gotham vs Palantir Foundry

Compared 7% of the time

SAP Data Services vs Palantir Foundry

Compared 6% of the time

AWS Glue vs Palantir Foundry

Compared 4% of the time

MuleSoft Anypoint Platform 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 13% of the time

Snowflake vs Teradata

Compared 8% of the time

MySQL vs Teradata

Compared 8% of the time

Vertica vs Teradata

Compared 5% of the time

More Teradata Competitors

Product Reports

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Palantir Foundry

December 2024

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November 2024

Also Known As

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

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Palantir

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

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

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