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Dremio vs IBM Watson Studio comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Dremio
Ranking in Data Science Platforms
8th
Average Rating
8.6
Reviews Sentiment
5.9
Number of Reviews
6
Ranking in other categories
Cloud Data Warehouse (10th)
IBM Watson Studio
Ranking in Data Science Platforms
12th
Average Rating
8.2
Reviews Sentiment
8.0
Number of Reviews
13
Ranking in other categories
AI Development Platforms (9th)
 

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 Dremio is 4.1%, up from 2.1% compared to the previous year. The mindshare of IBM Watson Studio is 2.1%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Enhancing survey analysis that provides valued insightfulness
I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.
MikeWalker - PeerSpot reviewer
It enables you to manage changes more effectively than any other platform.
Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it. There's another thing called data providence. They're tied together. Data providence allows you to go back and recreate the data at any particular point in time. It's extremely important for compliance and governance issues because data changes all time. How did it change? What was it three days or months ago? You may have made some decisions based on data that was three months old, so you might need to revisit those. It's essential for things like machine learning and deep learning, where you are generating AI models off data. When the model stops working or doesn't work as expected, you need to figure out why. You have to go back and adjust the datasets used to train the model. We do that through an open-source project called Nessie, which is their basis for providing data lineage and data province capabilities. It's super powerful. Arrow is another open-source project for storing data in memory and performing data query operations. Data sits on a disk in one format. If you want to do anything with data, you have to load it into your computer and put it into memory so you can work with it. Arrow provides a format in memory that enables the whole library to perform various operations on that data. Every vendor has its own way of representing data in memory. They've latched onto an industry standard and developed it so it's open. Now people can use the exact same format in memory to do operations and use the library set to perform functions on data. New developers can decide if they want to develop their own memory format or use one that's already there. Data transfer is a massive problem when you're working with large datasets, doing advanced analytics, and trying to train machine learning or deep learning models. What happens often is companies downsample their data sets to do training on models because transferring and managing data on a deep learning or machine learning platform is too much.
Abilio Duarte - PeerSpot reviewer
A highly robust and well-documented platform that simplifies the complex world of AI
The main challenge lies in visibility and ease of use. Providing training sessions can be immensely helpful in helping users navigate and understand the tool's potential. This approach would empower users to explore and make the most of the tools and technologies at their disposal. Another area where IBM could enhance its offering is by providing more visibility to end users regarding the vast potential that Watson offers.

Quotes from Members

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

Pros

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"It offers very good visualization."
"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"You can quickly build models because it does the work for you."
"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."
"Most of the product features are good but I particularly like the linear regression analysis."
"SPSS is quite robust and quicker in terms of providing you the output."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio allows querying the files I have on my block storage or object storage."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"We primarily use Dremio to create a data framework and a data queue."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"It has greatly improved the performance because it is standardized across the company."
"Stability-wise, it is a great tool."
"Watson Studio is very stable."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"IBM Watson Studio consistently automates across channels."
"It is a stable, reliable product."
"The system's ability to take a look at data, segment it and then use that data very differently."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
 

Cons

"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."
"IBM SPSS Statistics could improve the visual outputs where you are producing, for example, a graph for a company board of directors, or an advert."
"I think the visualization and charting should be changed and made easier and more effective."
"The reports could be better."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"This solution is not suitable for use with Big Data."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"It shows errors sometimes."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"So a better user interface could be very helpful"
"We would like to see it more web-based with more functionality."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"I want IBM's technical support team to provide more specific answers to queries."
"I think maybe the support is an area where it lacks."
"The initial setup was complex."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"Some of the solutions are really good solutions but they can be a little too costly for many."
 

Pricing and Cost Advice

"More affordable training for new staff members."
"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."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"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."
"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 this solution is a little bit high, which was a problem for my company."
"Dremio is less costly competitively to Snowflake or any other tool."
"Right now the cluster costs approximately $200,000 per month and is based on the volume of data we have."
"Watson Studio's pricing is reasonable for what you get."
"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
"IBM Watson Studio is an expensive solution."
"IBM Watson Studio is a reasonably priced product"
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
University
9%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
32%
Computer Software Company
10%
Manufacturing Company
8%
Retailer
4%
Financial Services Firm
14%
Computer Software Company
12%
Manufacturing Company
9%
University
8%
 

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.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...
What needs improvement with IBM SPSS Statistics?
IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...
What do you like most about Dremio?
Dremio allows querying the files I have on my block storage or object storage.
What is your experience regarding pricing and costs for Dremio?
Every tool has a value based on its visualization, and the pricing is worth its value.
What needs improvement with Dremio?
Dremio's interface is good, but it has a few limitations. I cannot do a lot of things with ANSI SQL or basic SQL. I c...
What needs improvement with IBM Watson Studio?
From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment a...
 

Also Known As

SPSS Statistics
No data available
Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
 

Learn More

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Overview

 

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
UBS, TransUnion, Quantium, Daimler, OVH
GroupM, Accenture, Fifth Third Bank
Find out what your peers are saying about Dremio vs. IBM Watson Studio and other solutions. Updated: October 2024.
816,406 professionals have used our research since 2012.