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Palantir Foundry vs Spring Cloud Data Flow comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Palantir Foundry
Ranking in Data Integration
12th
Average Rating
7.6
Reviews Sentiment
7.2
Number of Reviews
15
Ranking in other categories
IT Operations Analytics (4th), Supply Chain Analytics (1st), Cloud Data Integration (10th), Data Migration Appliances (3rd), Data Management Platforms (DMP) (1st), Data and Analytics Service Providers (1st)
Spring Cloud Data Flow
Ranking in Data Integration
22nd
Average Rating
7.8
Reviews Sentiment
6.7
Number of Reviews
9
Ranking in other categories
Streaming Analytics (10th)
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Palantir Foundry is 2.5%, down from 3.1% compared to the previous year. The mindshare of Spring Cloud Data Flow is 1.1%, up from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

Manilal Kasera - PeerSpot reviewer
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.
NitinGoyal - PeerSpot reviewer
Has a plug-and-play model and provides good robustness and scalability
The solution's community support could be improved. I don't know why the Spring Cloud Data Flow community is not very strong. Community support is very limited whenever you face any problem or are stuck somewhere. I'm not sure whether it has improved in the last six months because this pipeline was set up almost two years ago. I struggled with that a lot. For example, there was limited support whenever I got an exception and sought help from Stack Overflow or different forums. Interacting with Kubernetes needs a few certificates. You need to define all the certificates within your application. With the help of those certificates, your Java application or Spring Cloud Data Flow can interact with Kubernetes. I faced a lot of hurdles while placing those certificates. Despite following the official documentation to define all the replicas, readiness, and liveliness probes within the Spring Cloud Data Flow application, it was not working. So, I had to troubleshoot while digging in and debugging the internals of Spring Cloud Data Flow at that time. It was just a configuration mismatch, and I was doing nothing weird. There was a small spelling difference between how Spring Cloud Data Flow was expecting it and how I passed it. I was just following the official documentation.

Quotes from Members

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

Pros

"It is easy to map out a workflow and run trigger-based scripts without having to deploy to another server."
"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."
"I like the data onboarding to Palantir Foundry and ETL creation."
"The data lineage is great."
"The solution offers very good end-to-end capabilities."
"The interface is really user-friendly."
"It's scalable."
"The most valuable features of Spring Cloud Data Flow are the simple programming model, integration, dependency Injection, and ability to do any injection. Additionally, auto-configuration is another important feature because we don't have to configure the database and or set up the boilerplate in the database in every project. The composability is good, we can create small workloads and compose them in any way we like."
"The solution's most valuable feature is that it allows us to use different batch data sources, retrieve the data, and then do the data processing, after which we can convert and store it in the target."
"The dashboards in Spring Cloud Dataflow are quite valuable."
"There are a lot of options in Spring Cloud. It's flexible in terms of how we can use it. It's a full infrastructure."
"The most valuable feature is real-time streaming."
"The best thing I like about Spring Cloud Data Flow is its plug-and-play model."
"The product is very user-friendly."
"The ease of deployment on Kubernetes, the seamless integration for orchestration of various pipelines, and the visual dashboard that simplifies operations even for non-specialists such as quality analysts."
 

Cons

"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."
"There is not a wide user base for the solution's online documentation so it is sometimes difficult to find answers."
"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."
"The solution could use more online documentation for new users."
"Cost of this solution is quite high."
"Difficult to receive data from external sources."
"The solution's visualization and analysis could be improved."
"Compared to other hyperscalers, Palantir Foundry is complex and not so user-intuitive."
"Spring Cloud Data Flow could improve the user interface. We can drag and drop in the application for the configuration and settings, and deploy it right from the UI, without having to run a CI/CD pipeline. However, that does not work with Kubernetes, it only works when we are working with jars as the Spring Cloud Data Flow applications."
"There were instances of deployment pipelines getting stuck, and the dashboard not always accurately showing the application status, requiring manual intervention such as rerunning applications or refreshing the dashboard."
"Spring Cloud Data Flow is not an easy-to-use tool, so improvements are required."
"The configurations could be better. Some configurations are a little bit time-consuming in terms of trying to understand using the Spring Cloud documentation."
"The solution's community support could be improved."
"Some of the features, like the monitoring tools, are not very mature and are still evolving."
"I would improve the dashboard features as they are not very user-friendly."
"On the tool's online discussion forums, you may get stuck with an issue, making it an area where improvements are required."
 

Pricing and Cost Advice

"Palantir Foundry has different pricing models that can be negotiated."
"The solution’s pricing is high."
"Palantir Foundry is an expensive solution."
"It's expensive."
"If you want support from Spring Cloud Data Flow there is a fee. The Spring Framework is open-source and this is a free solution."
"The solution provides value for money, and we are currently using its community edition."
"This is an open-source product that can be used free of charge."
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Top Industries

By visitors reading reviews
Manufacturing Company
14%
Financial Services Firm
11%
Computer Software Company
10%
Government
7%
Financial Services Firm
29%
Computer Software Company
17%
Manufacturing Company
7%
Retailer
6%
 

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. ...
What needs improvement with Spring Cloud Data Flow?
I would improve the dashboard features as they are not very user-friendly. Another area for improvement is the documentation, as it is not very precise. There are limited resources available on Spr...
What is your primary use case for Spring Cloud Data Flow?
I am a developer using Spring Cloud Dataflow. We primarily use it to convert our applications from monolithic to microservices. The solution is used for scheduling tasks in a specific order and ens...
What advice do you have for others considering Spring Cloud Data Flow?
My advice would be to thoroughly review the documentation and understand if Spring Cloud Dataflow is the right solution for your application. For applications with only one or two microservices, it...
 

Learn More

 

Overview

 

Sample Customers

Merck KGaA, Airbus, Ferrari,United States Intelligence Community, United States Department of Defense
Information Not Available
Find out what your peers are saying about Palantir Foundry vs. Spring Cloud Data Flow and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.