Palantir Foundry vs StreamSets comparison

Palantir and IBM are both solutions in the Data Integration category. Palantir is ranked #19 with an average rating of 7.0, while IBM is ranked #15 with an average rating of 8.4. Palantir holds a 2.8% mindshare in DI, compared to IBM’s 1.6% mindshare. Additionally, 86% of Palantir users are willing to recommend the solution, compared to 100% of IBM users who would recommend it.

Palantir Foundry

Read 15 Palantir Foundry reviews

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3,034 Comparison Views

86% willing to recommend

StreamSets

Read 21 StreamSets reviews

2,378 Views
1,645 Comparison Views

100% willing to recommend

Palantir Foundry

StreamSets

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 19, 2024

StreamSets and Palantir Foundry compete in the data integration and pipeline management category. StreamSets has the upper hand due to its ease of use and configuration flexibility without extensive coding skill requirements.

Features: StreamSets offers ease of configuration with numerous connectors and a graphical interface, allowing the creation of data pipelines without coding. It includes features like data drift management and integration with Hadoop and Snowflake. Palantir Foundry provides integrated data visualization, comprehensive data lineage tracking, and robust real-time integration capabilities, making it a powerful end-to-end data solution.

Room for Improvement: StreamSets may improve its integration with non-Java platforms and enhance its user interface and logging capabilities. Addressing its complexity and refining the security model could benefit users. Palantir Foundry is often critiqued for its high expense and steep learning curve, with a need for better documentation and user experience improvements for non-technical users.

Ease of Deployment and Customer Service: StreamSets supports flexible deployments across various environments, with generally positive customer service but occasional variability in response times. Palantir Foundry, being largely cloud-based, offers a streamlined deployment process but receives mixed reviews on support, often relying on community resources.

Pricing and ROI: StreamSets offers diverse pricing models, including a free version, with significant ROI through reduced development time. Its extensive features can be expensive for smaller businesses. Palantir Foundry's high cost is offset by its integrated capabilities eliminating the need for multiple tools, although cost remains a concern for small enterprises seeking quick ROI.

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

Buyer's Guide

Palantir Foundry vs. StreamSets

February 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)

StreamSets

Ranking in Data Integration

15th

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Palantir Foundry is 2.8%, up from 2.7% compared to the previous year. The mindshare of StreamSets is 1.6%, up from 1.3% 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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Nantabo Jackie

Sales Manager at Soft Hostings Limited

Simplified pipelines and helped us break down data silos within our organization

The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

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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

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

"It's scalable."

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

"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."

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

"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."

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

More Palantir Foundry pros

"The best feature that I really like is the integration."

"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."

"In StreamSets, everything is in one place."

"The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"

"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."

"StreamSets is the leader in the market."

"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."

More StreamSets pros

Cons

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

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

"Some error messages can be very cryptic."

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

"The workflow could be improved."

"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 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."

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

More Palantir Foundry cons

"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."

"The software is very good overall. Areas for improvement are the error logging and the version history. I would like to see better, more detailed error logging information."

"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."

"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."

"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."

"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."

"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."

"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."

More StreamSets cons

Pricing and Cost Advice

"Palantir Foundry is an expensive solution."

"It's expensive."

"The solution’s pricing is high."

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

"The pricing is affordable for any business."

"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."

"The licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."

"StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"It's not so favorable for small companies."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Manufacturing Company

14%

Computer Software Company

11%

Financial Services Firm

10%

Government

Financial Services Firm

14%

Computer Software Company

11%

Manufacturing Company

10%

Insurance 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.

See all answers

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.

See all answers

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. ...

See all answers

What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

See all answers

What needs improvement with StreamSets?

We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...

See all answers

What is your primary use case for StreamSets?

StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...

See all answers

Comparisons

Azure Data Factory vs Palantir Foundry

Compared 9% of the time

Palantir Gotham vs Palantir Foundry

Compared 5% of the time

SAP Data Services vs Palantir Foundry

Compared 5% of the time

Domo vs Palantir Foundry

Compared 4% of the time

Aera vs Palantir Foundry

Compared 4% of the time

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Informatica PowerCenter vs StreamSets

Compared 14% of the time

IBM InfoSphere DataStage vs StreamSets

Compared 12% of the time

webMethods.io vs StreamSets

Compared 9% of the time

Fivetran vs StreamSets

Compared 8% of the time

Azure Data Factory vs StreamSets

Compared 7% of the time

More StreamSets Competitors

Product Reports

Buyer's Guide

Palantir Foundry

March 2025

Download Palantir Foundry product report

Buyer's Guide

StreamSets

March 2025

Download StreamSets product report

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

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

IBM

Sample Customers

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

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

Palantir Foundry vs. StreamSets

February 2025

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