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Fivetran vs Palantir Foundry comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 3, 2024

Review summaries and opinions

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

ROI

Sentiment score
6.6
Fivetran offers significant time and cost-saving benefits, simplifying data integration and maintenance while reducing reliance on data engineers.
Sentiment score
5.0
Palantir Foundry users reported faster implementation, increased efficiency, streamlined processes, enhanced resources, and improved productivity with comprehensive tools.
Fivetran provides time savings, cost reductions, and improvements in data quality.
Team Lead Data Engineer at Data Pilot
It saves us the effort of having one to two data engineers managing the tasks that Fivetran handles.
Lead Data Engineer at Sensilab
With traditional development requiring many specialized roles, Palantir Foundry allows us to operate efficiently with fewer personnel.
Data Engineering Specialist at LTM
We saved approximately 20 to 35 percent in man-hours needed and the timing improved our project timelines by approximately 50 to 55 percent.
Consultant at a tech vendor with 1,001-5,000 employees
One clear example was the pipeline optimization I mentioned, where we reduced execution time by thirty to forty percent.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
 

Customer Service

Sentiment score
6.0
Fivetran customer support is efficient yet sometimes slow, rated 7-9, with calls for improved critical issue communication.
Sentiment score
6.2
Palantir Foundry's support is praised for responsiveness and knowledge, though experiences vary; documentation aids self-resolution effectively.
If they could provide support more quickly, that would be great.
Manager at InfoCepts
The technical support provided by Fivetran has generally been good, with a response time and competence that I would rate as good.
Lead Data Engineer at Sensilab
Customer support from Fivetran is quite good; it's really nice and responsive.
Team Lead Data Engineer at Data Pilot
They are knowledgeable, and their boot camps demonstrate solutions in just three days, which typically takes months or years.
Enterprise Architect at a mining and metals company with 10,001+ employees
When I seek help regarding code in Slate, it can take considerable time for the team to find the right answer or documentation, especially since the responses depend on the level of support provided, and specific queries regarding coding usually require reaching out to more experienced developers.
Data Analyst at BP Exploration Caspian Sea Ltd
The support staff are extremely knowledgeable and good at what they are doing.
Operations And Integration Chief at a aerospace/defense firm with 10,001+ employees
 

Scalability Issues

Sentiment score
7.1
Fivetran scales well for various businesses, accommodating data needs but can be costly and complex for smaller enterprises.
Sentiment score
6.1
Palantir Foundry offers flexibility and scalability, efficiently managing large data, though costs and configuration may impact performance.
Fivetran's scalability has been tested effectively, and it has been working well for our organization's growing data needs.
Team Lead Data Engineer at Data Pilot
We work with large volumes of healthcare data, and it has been able to handle all the large-scale ingestion, transformation, and distributed processing workflows effectively.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
For scalability, I would rate it ten out of ten because you have a lot of flexibility.
Associate Vice President at a insurance company with 10,001+ employees
Regarding scalability, if you have billions and trillions of records, Palantir Foundry accommodates ETL pipelines with a dedicated compute profile.
Data Engineering Specialist at LTM
 

Stability Issues

Sentiment score
8.0
Users generally express high satisfaction with Fivetran's stable reliability, despite occasional issues with API connections and custom setups.
Sentiment score
7.6
Palantir Foundry is stable, with occasional issues in data handling, praised for scalability, and generally well-regarded for reliability.
They have 99.9% accuracy on the data load and they maintain transparency.
Manager at InfoCepts
In my experience, Fivetran is stable with very few instances of downtime or reliability issues.
Team Lead Data Engineer at Data Pilot
During the duration of the time that we used Fivetran, it was highly stable.
Founder at a marketing services firm with 1-10 employees
Live data streaming is very hard and it keeps breaking, so it is not very stable and depends a lot on the satellite network.
Product Manager
I get more technical support from Palantir.
Data Development Manager at a healthcare company with 5,001-10,000 employees
Palantir Foundry has been a stable and reliable enterprise platform.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
 

Room For Improvement

Fivetran needs improvements in connectors, real-time processing, user interface, pricing, support, documentation, and integration capabilities.
Palantir Foundry users seek better documentation, reduced costs, performance improvements, enhanced UI, and increased flexibility in data integration.
From a cost perspective, if the number of connectors is lesser, then Fivetran is not the most cost-efficient option.
Founder at a marketing services firm with 1-10 employees
I want more flexibility during ingestion, specifically for transformations needed beforehand.
Team Lead Data Engineer at Data Pilot
Fivetran could improve by adapting more for technical users and by providing more options for such users.
Lead Data Engineer at Sensilab
The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
I want to build conversational BI or conversational agents quickly that can connect to MCPs, and other MCPs that I can communicate with in Palantir Foundry, which are areas to advance forward.
Principal Architect at HCLTech
An improvement would be that in case of any changes done by the Palantir team, those changes need to be tested thoroughly so there are no downstream impacts, ensuring that the business is not affected by any modifications in the system.
Engineer, Data Engineering at GlobalFoundries
 

Setup Cost

Fivetran's pricing is high, favoring larger enterprises with discounts available; smaller companies may find it prohibitive.
Palantir Foundry's high initial costs deter some, but it's cost-effective long-term; pricing varies for larger enterprises.
Our current yearly contract for Fivetran is approximately $70,000.
Lead Data Engineer at Sensilab
Its high initial pricing can be intimidating, but it becomes cost-effective as it reduces the need for a development team.
Enterprise Architect at a mining and metals company with 10,001+ employees
In terms of getting a contractor to work on that, I would probably say it is more expensive because there are fewer people with that skillset compared to, say, Databricks or Azure.
Data Development Manager at a healthcare company with 5,001-10,000 employees
We can consult it in the right way regarding Palantir Foundry use, as it is still a gray area right now concerning costing.
Principal Architect at HCLTech
 

Valuable Features

Fivetran is valued for seamless data replication, user-friendly interface, scalability, and minimal coding, enabling efficient data handling.
Palantir Foundry enhances productivity with data modeling, AI integration, security, and collaborative tools for seamless multi-source integration.
The most valuable feature of Fivetran is its built-in connectors for a wide range of data sources.
Lead Data Engineer at Sensilab
The real-time data replication is what I see best in the market where it reduces the overhead of customers needing to maintain the pipeline.
Manager at InfoCepts
The ability to seamlessly integrate with a large variety of data sources is valuable.
Founder at a marketing services firm with 1-10 employees
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.
Architect at L&T Technology Services
The main advantage is you can decentralize the analytics, and you will have everything in one place, so that you do not need to rely on multiple departments working on different tools.
Associate Vice President at a insurance company with 10,001+ employees
The low-code solutions made our lives easier because not everybody is too technical to get started and the barrier to entry is very low.
Consultant at a tech vendor with 1,001-5,000 employees
 

Categories and Ranking

Fivetran
Ranking in Data Integration
13th
Ranking in Cloud Data Integration
9th
Average Rating
8.2
Reviews Sentiment
6.8
Number of Reviews
29
Ranking in other categories
Data Replication (3rd)
Palantir Foundry
Ranking in Data Integration
5th
Ranking in Cloud Data Integration
4th
Average Rating
8.0
Reviews Sentiment
6.4
Number of Reviews
59
Ranking in other categories
IT Operations Analytics (5th), Supply Chain Analytics (1st), Data Migration Appliances (2nd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
 

Mindshare comparison

As of June 2026, in the Data Integration category, the mindshare of Fivetran is 1.8%, down from 2.3% compared to the previous year. The mindshare of Palantir Foundry is 2.0%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration Mindshare Distribution
ProductMindshare (%)
Palantir Foundry2.0%
Fivetran1.8%
Other96.2%
Data Integration
 

Featured Reviews

Hafiz Usman - PeerSpot reviewer
Team Lead Data Engineer at Data Pilot
Has accelerated data integration workflows and supports seamless development of custom connectors
I've worked extensively with Fivetran, mainly used for extraction purposes, and I've worked with the transformation element in it as well. Fivetran not only has built-in connectors but also provides SDK connectors, allowing us to develop our own connectors in an easy manner. I don't have to write raw Python scripts or dumping scripts; it offers straightforward examples and guidelines, making it much simpler to develop custom connectors inside Fivetran. We've been able to develop many custom connectors as well, which is unique and beneficial for having everything centralized instead of having those connectors located elsewhere. One of the best features by Fivetran is its clean, simple, and intuitive UI. It includes a transformation section where I can deploy my DBT queries and scripts. It also supplies good tracking capabilities for billing estimates and user permissions, allowing for customization to the desired level. The number of connectors it has remains a standout feature, and within connectors, the options available are very helpful. Although it sometimes appears static due to its built-in nature, it offers good flexibility for data transformation and caching, which I appreciate because it saves us extensive script-writing time.
reviewer2846265 - PeerSpot reviewer
PALANTIR DATA ENGINEER at a healthcare company with 10,001+ employees
Unified healthcare pipelines have improved data trust and accelerated operational decisions
One challenge regarding how Palantir Foundry can be improved is the learning curve. Foundry has a very broad ecosystem with Ontology, Pipeline Builder, Code Repositories, and AI integrations. For new engineers or business users onboarding, it can take time, especially if they are coming from more traditional data platforms. Better documentation, simplified onboarding paths, and more beginner-friendly examples would help accelerate adoption. Another area is debugging complexity. While lineage and monitoring are strong features, troubleshooting deeply interconnected pipelines can still become difficult in a large enterprise environment. Sometimes error logs and pipeline failure messages could be more descriptive or developer-friendly, especially for distributed PySpark jobs. Another pain point is customization limitations in certain UI-driven components. While low-code tools are great for rapid development, highly customized workflows sometimes still require engineering workarounds or deeper technical implementation. The platform is extremely capable, but improvements around usability, debugging experience, DevOps flexibility, and ecosystem openness would make it even more effective for enterprise engineering teams.
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Top Industries

By visitors reading reviews
Financial Services Firm
13%
Manufacturing Company
10%
Computer Software Company
9%
Healthcare Company
6%
Manufacturing Company
14%
Financial Services Firm
9%
Government
7%
University
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise7
Large Enterprise16
By reviewers
Company SizeCount
Small Business11
Midsize Enterprise7
Large Enterprise49
 

Questions from the Community

What's the deal with the HVR software acquisition?
As a user of HVR Software I followed this deal closely. Fivetran is apparently trying to establish more in its sector and by buying an already established data replication software, they become som...
Does HVR Software provide reliable insights?
I honestly can't think of another data replication software that can give you better statistics and insight than HVR Software. There's the feature for topology and statistics and both of them can ...
How much traffic can HVR Software handle?
As someone who works at a company where a high volume of information is replicated and has tried several data replication softwares, I can tell you that you're looking at the right one. HVR Softwar...
What needs improvement with Palantir Foundry?
One challenge regarding how Palantir Foundry can be improved is the learning curve. Foundry has a very broad ecosystem with Ontology, Pipeline Builder, Code Repositories, and AI integrations. For n...
What is your primary use case for Palantir Foundry?
I use Palantir Foundry for my primary use case, which involves building and maintaining end-to-end pipelines and operational data products at UHG for our healthcare analytics team. I work on data i...
What advice do you have for others considering Palantir Foundry?
My advice would be to approach Palantir Foundry as an enterprise operational platform, not just a traditional data tool. The platform delivers the most value when organizations fully leverage its g...
 

Overview

 

Sample Customers

Autodesk, Condé Nast, JetBlue, Morgan Stanley, OpenAI, LVMH, Pfizer, Verizon, SpotifyNational Australia Bank, Saks, Cemex, Okta, Dropbox, Pitney Bowes, World Fuel Services,Lufthansa, AutoZone, ASICS, ASOS, Coupa, Databricks, Hermes, New Relic, Intercom,Canva, Honeywell, Square, DocuSign, Nandos, Oldcastle Infrastructure
Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Find out what your peers are saying about Fivetran vs. Palantir Foundry and other solutions. Updated: June 2026.
900,644 professionals have used our research since 2012.