Amazon SageMaker vs TIBCO Data Science comparison

Amazon Web Services (AWS) and TIBCO are both solutions in the Data Science Platforms category. Amazon Web Services (AWS) is ranked #3 with an average rating of 8.0, while TIBCO is ranked #25. Amazon Web Services (AWS) holds a 7.3% mindshare in Data Science Platforms, compared to TIBCO’s 0.6% mindshare. Additionally, 91% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

Amazon SageMaker

Read 36 Amazon SageMaker reviews

6,112 Views
4,892 Comparison Views

91% willing to recommend

TIBCO Data Science

Read 4 TIBCO Data Science reviews

335 Views
255 Comparison Views

100% willing to recommend

Amazon SageMaker

TIBCO Data Science

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 5, 2024

TIBCO Data Science and Amazon SageMaker are platforms competing in data science and machine learning. While TIBCO Data Science excels in intuitive use and support, Amazon SageMaker holds the upper hand with its robust features and integration, offering greater perceived value.

Features: TIBCO Data Science provides intuitive analytic capabilities, visual workflows, and strong enterprise integration. In contrast, Amazon SageMaker offers comprehensive model training and deployment automation, extensive machine learning tools, and seamless AWS integration.

Room for Improvement: TIBCO Data Science could enhance its scalability, improve automation in model deployment, and offer more advanced machine learning tools. Amazon SageMaker might work on reducing its learning curve, improving customer support response times, and offering more competitive pricing.

Ease of Deployment and Customer Service: TIBCO Data Science provides straightforward deployment and responsive support, simplifying entry into data science projects. Amazon SageMaker, leveraging AWS infrastructure, allows for streamlined deployment with vast resources but involves a steeper learning curve.

Pricing and ROI: TIBCO Data Science is more affordable with lower initial setup costs, delivering quick ROI through its straightforward application. Amazon SageMaker, despite the higher upfront investment, offers extensive functionality and flexibility, leading to substantial long-term ROI.

To learn more, read our detailed Amazon SageMaker vs. TIBCO Data Science Report (Updated: March 2025).

Buyer's Guide

Amazon SageMaker vs. TIBCO Data Science

March 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

Amazon SageMaker

Ranking in Data Science Platforms

3rd

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

AI Development Platforms (5th)

TIBCO Data Science

Ranking in Data Science Platforms

25th

Average Rating

7.6

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Amazon SageMaker is 7.3%, down from 9.8% compared to the previous year. The mindshare of TIBCO Data Science is 0.6%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Hemant Paralkar

Lead Consultant at Saama

Improves team collaboration with advanced feature sharing but needs a better user experience

Improvement is needed in the no-code and low-code capabilities of Amazon SageMaker. This would empower citizen data scientists to utilize the tool more effectively since many data scientists do not have a core development background. Additionally, dealing with frequent UI updates can be challenging, especially for infrastructure architects like myself. It involves effort to migrate to new UIs, making the updates not seamless. User auditing requires enhancements as tracking operations performed by users can be difficult due to dynamic IP validation and role propagation.

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Veeresh-SHRINGARI

Portfolio Manager, AI & ML at a healthcare company with 10,001+ employees

A straightforward initial setup and good reporting but needs better documentation

It would be ideal if it could be put onto the NMP where you can make more of an analysis. Right now, people don't have enough time to go through the report and make an analysis. It should provide the information of what is on the report into some kind of a dialogue form. Then, a person can ask certain questions and it could interactively give the required report. In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues. If you are doing certain operations of RDBMS, you suffer in terms of the latency of the data. That can be improved upon. Users should be able to cross tables of the web pages they are developing on Spotfire and this needs to be really easy and convenient. Right now, you need to do a lot of tweaks. The solution should be more user-friendly and require fewer tweaks, extensions, and workarounds.

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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 Autopilot feature is really good because it's helpful for people who don't have much experience with coding or data pipelines. When we suggest SageMaker to clients, they don't have to go through all the steps manually. They can leverage Autopilot to choose variables, run experiments, and monitor costs. The results are also pretty accurate."

"I appreciate the ease of use in Amazon SageMaker."

"Amazon SageMaker is highly valuable for managing ML workloads. It connects to AWS cloud resources, making it easy to deploy algorithms and collaborate using tools like GitLab. It offers a wide range of Python libraries and other necessary tools for modelling and algorithms."

"The most valuable features in Amazon SageMaker are its AutoML, feature store, and automated hyperparameter tuning capabilities."

"The most valuable feature of Amazon SageMaker is SageMaker Studio."

"The feature I found most valuable is the data catalog, as it assists with the lineage of data through the preparation pipeline."

"The support is very good with well-trained engineers whose training curriculum is rigorous."

"The solution's ability to improve work at my organization stems from the ensemble model and a combination of various models it provides."

More Amazon SageMaker pros

"The idea that you don't have to generate reports each day but they are sent automatically is great."

"The most valuable feature is the ease of setting up visualizations."

"The most valuable feature is the performance."

"We like the way we can drill down into each report to get back data on each project. From the portfolio level, I can see what is happening on it. That is a really important feature. I can look at indirect costs, for example, which are hitting each CIO portfolio. It's good to be able to see actual resources in terms of time as well as cost."

Cons

"Having all documentation easily accessible on the front page of SageMaker would be a great improvement."

"I would say the IDE is quite immature, but it is still in its infancy, so I expect it to get better over time."

"The solution needs to be cheaper since it now charges per document for extraction."

"There are other better solutions for large data, such as Databricks."

"Amazon SageMaker can make it simpler to manage the data flow from start to finish, such as by integrating data, usingthe machine, and deploying models. This process could be more user-friendly compared to other tools. I would also like to improve integration with Bedrock and the LLM connection for AWS."

"Scalability to handle big data can be improved by making integration with networks such as Hadoop and Apache Spark easier."

"The platform could be more accessible to users with basic coding skills, making it more intuitive and easier for beginners to use comfortably."

"The main challenge with Amazon SageMaker is the integrations."

More Amazon SageMaker cons

"In terms of performance, I can see there are some issues when you are working with big data. When we are taking it from the Data Lake, we have a lot of issues."

"Additional templates would help to get things moving more quickly in terms of getting the reports out."

"I would like the visualization for the map of countries to be more easily configurable."

"The scripting for customization could be improved."

Pricing and Cost Advice

"The solution is relatively cheaper."

"There is no license required for the solution since you can use it on demand."

"Databricks solution is less costly than Amazon SageMaker."

"I rate the pricing a five on a scale of one to ten, where one is the lowest price, and ten is the highest price. The solution is priced reasonably. There is no additional cost to be paid in excess of the standard licensing fees."

"On average, customers pay about $300,000 USD per month."

"The pricing is complicated as it is based on what kind of machines you are using, the type of storage, and the kind of computation."

"The tool's pricing is reasonable."

"In terms of pricing, I'd also rate it ten out of ten because it's been beneficial compared to other solutions."

More Amazon SageMaker pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Educational Organization

13%

Computer Software Company

11%

Manufacturing Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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Questions from the Community

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

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What do you like most about Amazon SageMaker?

We've had experience with unique ML projects using SageMaker. For example, we're developing a platform similar to ChatGPT that requires models. We utilize Amazon SageMaker to create endpoints for t...

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What is your experience regarding pricing and costs for Amazon SageMaker?

Before deploying SageMaker, I reviewed the pricing, especially for notebook instances. The cost for small to medium instances is not very high.

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Comparisons

Databricks vs Amazon SageMaker

Compared 17% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Dataiku vs Amazon SageMaker

Compared 10% of the time

Google Vertex AI vs Amazon SageMaker

Compared 9% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

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Databricks vs TIBCO Data Science

Compared 52% of the time

More TIBCO Data Science Competitors

Product Reports

Buyer's Guide

Amazon SageMaker

March 2025

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Buyer's Guide

Data Science Platforms

March 2025

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Also Known As

AWS SageMaker, SageMaker

Alpine Data Chorus

Overview

Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.

Amazon Web Services (AWS)

TIBCO Spotfire Data Science is an enterprise big data analytics platform that can help your organization become a digital leader. The collaborative user-interface allows data scientists, data engineers, and business users to work together on data science projects. These cross-functional teams can build machine learning workflows in an intuitive web interface with a minimum of code, while still leveraging the power of big data platforms.

TIBCO

Sample Customers

DigitalGlobe, Thomson Reuters Center for AI and Cognitive Computing, Hotels.com, GE Healthcare, Tinder, Intuit

Havas Media, Tipping Point Community, eviCore

Buyer's Guide

Amazon SageMaker vs. TIBCO Data Science

March 2025

Free Report: Amazon SageMaker vs. TIBCO Data Science

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