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Databricks vs IBM Streams comparison

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Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 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 Streaming Analytics
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
94
Ranking in other categories
Cloud Data Warehouse (3rd), Data Science Platforms (1st), Data Management Platforms (DMP) (3rd)
IBM Streams
Ranking in Streaming Analytics
23rd
Average Rating
8.2
Reviews Sentiment
7.2
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2026, in the Streaming Analytics category, the mindshare of Databricks is 7.4%, down from 12.3% compared to the previous year. The mindshare of IBM Streams is 2.1%, up from 1.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Databricks7.4%
IBM Streams2.1%
Other90.5%
Streaming Analytics
 

Featured Reviews

SimonRobinson - PeerSpot reviewer
Governance And Engagement Lead
Improved data governance has enabled sensitive data tracking but cost management still needs work
I believe we could improve Databricks integration with cloud service providers. The impact of our current integration has not been particularly good, and it's becoming very expensive for us. The inefficiencies in our implementation, such as not shutting down warehouses when they're not in use or reserving the right number of credits, have led to increased costs. We made several beginner mistakes, such as not taking advantage of incremental loading and running overly complicated queries all the time. We should be using ETL tools to help us instead of doing it directly in Databricks. We need more experienced professionals to manage Databricks effectively, as it's not as forgiving as other platforms such as Snowflake. I think introducing customer repositories would facilitate easier implementation with Databricks.
Ahmed_Emad - PeerSpot reviewer
Territory Sales Leader at Sumerge
A solution for data pipelines but has connector limitations
We have used Kafka for seven years. IBM streams gives you many OOTB features that can boost the time-to-market, especially when it comes to reporting and monitoring for example. Confluent is recognized as one of the leaders in this space and the main reason for this is related to the complete vision of the platform also the large number of connectors. This gives the edge and competitive advatnage.

Quotes from Members

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

Pros

"Databricks helps crunch petabytes of data in a very short period of time for data scientists or business analysts, helping with fraud analysis, finance, projections, and more, which is exactly the purpose of big data and analytics."
"The time travel feature is the solution's most valuable aspect."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The fast data loading process and data storage capabilities are great."
"The solution is very easy to use."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."
"The capability of the product is quite good and we are very satisfied with it overall."
"Easy development and deployment, Java implementation features, and the real time analyser and alarm function are the most valuable features for us."
"As a result, the TELCO company was able to cut down the time it took to respond to customer needs and there were fewer complaints."
"The product has enabled us to create solutions to client problems that would have either been impossible or very expensive/difficult using other technologies."
"The OEM Solution (Excel-medical.com) running on top of IBM Streams provides real-time clinical algorithms that can give better insight into the patient's acuity, thus cutting off time to discharge patients and inversely making sure that sick patients don't get discharged until ready."
 

Cons

"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."
"However, the platform could become easier to use."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"A couple of times I faced an issue where a long-running process was consuming a lot of time and then stopped abruptly."
"Databricks can improve by making the documentation better."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"The solution could improve by providing better automation capabilities. For example, working together with more of a DevOps approach, such as continuous integration."
"In my opinion, areas of Databricks that have room for improvement involve the dashboards. Until recently, everyone used third-party systems such as Power BI to connect to Databricks for dashboards and reports, but they're now coming up with their IBI dashboard, and I think they're on the right track to improve that even further."
"We had some stability issues where we used embedded Zookeeper in production."
"I’d like to see a tool kit specifically targeted at incremental machine learning. It’s already great for scoring previously trained models, but dynamically updating models is currently more of a 'grow your own' kind of thing."
"The development IDE sometimes crashes and freezes."
"The price and versatility of this product need to improve - it is not inexpensive."
 

Pricing and Cost Advice

"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"I rate the price of Databricks as eight out of ten."
"I would rate Databricks' pricing seven out of ten."
"Price-wise, I would rate Databricks a three out of five."
"The price is okay. It's competitive."
"The pricing depends on the usage itself."
"The solution is affordable."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
Information not available
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Manufacturing Company
10%
Outsourcing Company
6%
Healthcare Company
6%
Government
16%
Financial Services Firm
15%
Construction Company
13%
Comms Service Provider
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business26
Midsize Enterprise12
Large Enterprise60
No data available
 

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...
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Comparisons

 

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
IBM InfoSphere Streams
 

Overview

 

Sample Customers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Globo TV, All England Lawn Tennis Club, CenterPoint Energy, Consolidated Communications Holdings, Darwin Ecosystem, Emory University Hospital, ICICI Securities, Irish Centre for Fetal and Neonatal Translational Research (INFANT), Living Roads, Mobileum, Optibus, Southern Ontario Smart Computing Innovation Platform (SOSCIP), University of Alberta, University of Montana, University of Ontario Institute of Technology, Wimbledon 2015
Find out what your peers are saying about Databricks vs. IBM Streams and other solutions. Updated: September 2026.
917,433 professionals have used our research since 2012.