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Databricks vs IBM Watson Studio comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

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

Databricks
Ranking in Data Science Platforms
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Streaming Analytics (1st)
IBM Watson Studio
Ranking in Data Science Platforms
12th
Average Rating
8.4
Reviews Sentiment
7.1
Number of Reviews
14
Ranking in other categories
AI Development Platforms (10th)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Databricks is 18.2%, down from 19.1% compared to the previous year. The mindshare of IBM Watson Studio is 1.9%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.
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

"It's easy to increase performance as required."
"Databricks has improved my organization by allowing us to transform data from sources to a different format and feed that to the analytics, business intelligence, and reporting teams. This tool makes it easy to do those kinds of things."
"I like how easy it is to share your notebook with others. You can give people permission to read or edit. I think that's a great feature. You can also pull in code from GitHub pretty easily. I didn't use it that often, but I think that's a cool feature."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"It's great technology."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"Databricks serves as a single platform for conducting the entire end-to-end lifecycle of machine learning models or AI ops."
"Specifically for data science and data analytics purposes, it can handle large amounts of data in less time. I can compare it with Teradata. If a job takes five hours with Teradata databases, Databricks can complete it in around three to three and a half hours."
"It is a very stable and reliable solution."
"Stability-wise, it is a great tool."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"It has greatly improved the performance because it is standardized across the company."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"The system's ability to take a look at data, segment it and then use that data very differently."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"It has a lot of data connectors, which is extremely helpful."
 

Cons

"I think setting up the whole account for one person and giving access are areas that can be difficult to manage and should be made a little easier."
"Performance could be improved."
"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."
"There could be more support for automated machine learning in the database. I would like to see more ways to do analysis so that the reporting is more understandable."
"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."
"The API deployment and model deployment are not easy on the Databricks side."
"One area that could be improved is the backup and restoration of the database and the overall database configuration."
"I think maybe the support is an area where it lacks."
"The main challenge lies in visibility and ease of use."
"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."
"So a better user interface could be very helpful"
"We would like to see it less as one big, massive product, but more based on smaller services that we can then roll out to consumers."
"One area that could be improved is the backup and restoration of the database and the overall database configuration."
"The initial setup was complex."
 

Pricing and Cost Advice

"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"The solution is a good value for batch processing and huge workloads."
"We only pay for the Azure compute behind the solution."
"Price-wise, I would rate Databricks a three out of five."
"The product pricing is moderate."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"IBM Watson Studio is a reasonably priced product"
"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."
"Watson Studio's pricing is reasonable for what you get."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
Financial Services Firm
15%
Computer Software Company
12%
Manufacturing Company
10%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
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...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
What is your experience regarding pricing and costs for IBM Watson Studio?
The pricing of Watson Studio is justified by the benefits and power it offers.
What needs improvement with IBM Watson Studio?
One area that could be improved is the backup and restoration of the database and the overall database configuration. There were also challenges with programming the network extension in the last p...
 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
GroupM, Accenture, Fifth Third Bank
Find out what your peers are saying about Databricks vs. IBM Watson Studio and other solutions. Updated: March 2025.
844,944 professionals have used our research since 2012.