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 #5 with an average rating of 7.6, while TIBCO is ranked #25. Amazon Web Services (AWS) holds a 7.7% mindshare in Data Science Platforms, compared to TIBCO’s 0.6% mindshare. Additionally, 88% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of TIBCO users who would recommend it.

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Executive Summary

We performed a comparison between Amazon SageMaker and TIBCO Data Science based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Amazon SageMaker vs. TIBCO Data Science Report (Updated: October 2024).

Buyer's Guide

Amazon SageMaker vs. TIBCO Data Science

October 2024

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Helped 814,649 peers since 2012

Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Amazon SageMaker is 7.7%, down from 10.4% compared to the previous year. The mindshare of TIBCO Data Science is 0.6%, up from 0.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Sep 21, 2023

Enhancing survey analysis that provides valued insightfulness

I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…

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Natu Lauchande

Tech Lead - Sanlam Fintech Cluster - Data,ML,AI Eng. at Sanlam

Feb 27, 2024

Easy to use and manage, but the documentation does not have a lot of information

We use the product for deploying machine learning models. We use it for the machine learning model development process We're currently implementing a project on a cross-selling model. It is like a standard XGBoost model. I’m evaluating the tool to see whether it will improve the workflow.…

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Veeresh-SHRINGARI

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

Dec 9, 2019

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 best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important."

"The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful."

"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."

"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."

"The learning curve to using this product is not steep. The program is appropriate for those who do not have a lot of background in programming, yet have to perform basic statistical analysis."

"in terms of the simplicity, I think the SPSS basic can handle it."

"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

More IBM SPSS Statistics pros

"They are doing a good job of evolving."

"The technical support of the tool was good."

"The most valuable feature of Amazon SageMaker is its integration. For example, AWS Lambda. Additionally, we can write Python code."

"I have contacted the solution's technical support, and they were really good. I rate the technical support a ten out of ten."

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

"We've had no problems with SageMaker's stability."

"The tool makes our ML model development a bit more efficient because everything is in one environment."

"The product aggregates everything we need to build and deploy machine learning models in one place."

More Amazon SageMaker pros

"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."

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

"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 performance."

Cons

"It could allow adding color to data models to make them easier to interpret."

"The solution needs more planning tools and capabilities."

"The technical support should be improved."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"The design of the experience can be improved."

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

"It could provide even more in the way of automation as there are many opportunities."

More IBM SPSS Statistics cons

"Amazon SageMaker could improve in the area of hyperparameter tuning by offering more automated suggestions and tips during the tuning process."

"While integration is available, there are concerns about how secure this integration is, particularly when exposing data to SageMaker."

"The model repository is a concern as models are stored on a bucket and there's an issue with versioning."

"Creating notebook instances for multiple users is pretty expensive in Amazon SageMaker."

"In my opinion, one improvement for Amazon SageMaker would be to offer serverless GPUs. Currently, we incur costs on an hourly basis. It would be beneficial if the tool could provide pay-as-you-go pricing based on endpoints."

"AI is a new area and AWS needs to have an internship training program available."

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

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

More Amazon SageMaker cons

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

"The scripting for customization could be improved."

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

"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."

Pricing and Cost Advice

"We think that IBM SPSS is expensive for this function."

"The price of this solution is a little bit high, which was a problem for my company."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

"It's quite expensive, but they do a special deal for universities."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

"The price of IBM SPSS Statistics could improve."

"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

More IBM SPSS Statistics pricing and cost advice

"The support costs are 10% of the Amazon fees and it comes by default."

"The product is expensive."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a six out of ten."

"SageMaker is worth the money for our use case."

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

"The cost offers a pay-as-you-go pricing model. It depends on the instance that you do."

"You don't pay for Sagemaker. You only pay for the compute instances in your storage."

"I would rate the solution's price a ten out of ten since it is very high."

More Amazon SageMaker pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Educational Organization

14%

Computer Software Company

11%

Manufacturing Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about IBM SPSS Statistics?

The software offers consistency across multiple research projects helping us with predictive analytics capabilities.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Statistics?

While the pricing of the product may be higher, the accompanying service and features justify the investment. However...

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What needs improvement with IBM SPSS Statistics?

In some cases, the product takes time to load a large dataset. They could improve this particular area.

See all answers

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 designe...

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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 Cha...

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

The license cost for Amazon SageMaker ranges between seven thousand to fifteen thousand dollars per month depending o...

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Comparisons

Alteryx vs IBM SPSS Statistics

Compared 14% of the time

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

SAS Analytics vs IBM SPSS Statistics

Compared 4% of the time

More IBM SPSS Statistics Competitors

Databricks vs Amazon SageMaker

Compared 28% of the time

Azure OpenAI vs Amazon SageMaker

Compared 12% of the time

Google Vertex AI vs Amazon SageMaker

Compared 11% of the time

Domino Data Science Platform vs Amazon SageMaker

Compared 7% of the time

Dataiku vs Amazon SageMaker

Compared 5% of the time

More Amazon SageMaker Competitors

TIBCO Statistica vs TIBCO Data Science

Compared 42% of the time

Dataiku vs TIBCO Data Science

Compared 27% of the time

More TIBCO Data Science Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

October 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Amazon SageMaker

November 2024

Download Amazon SageMaker product report

Buyer's Guide

Data Science Platforms

October 2024

Download TIBCO Data Science product report

Also Known As

SPSS Statistics

AWS SageMaker, SageMaker

Alpine Data Chorus

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IBM

Amazon Web Services (AWS)

TIBCO

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

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.

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.

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA

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

October 2024

Free Report: Amazon SageMaker vs. TIBCO Data Science

Find out what your peers are saying about Amazon SageMaker vs. TIBCO Data Science and other solutions. Updated: October 2024.

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