Amazon MSK vs Databricks comparison

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Amazon MSK

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Executive SummaryUpdated on Dec 17, 2024

Databricks and Amazon MSK serve different categories, with Databricks leading in data analytics and machine learning, and Amazon MSK leading in data streaming with Apache Kafka integration. Databricks might have an advantage in environments focusing on advanced analytics and machine learning capabilities, whereas Amazon MSK offers superior real-time data processing services.

Features: Databricks provides an integrated environment that supports multiple programming languages, collaborative notebooks, and machine learning integrations. It includes built-in optimization for data processing and interactive querying. Amazon MSK simplifies real-time stream management with a fully managed Kafka service, reducing administrative tasks and offering seamless integration with other AWS services.

Room for Improvement: For Databricks, improvements could be made in simplifying administrative setup, expanding multi-cloud compatibility, and enhancing cost transparency in data processing. For Amazon MSK, enhancements might include broadening support for custom integrations outside of AWS, improving user interfaces for complex setups, and optimizing latency for large-scale streaming environments.

Ease of Deployment and Customer Service: Databricks offers deployment across various cloud environments and is praised for effective customer support. In comparison, Amazon MSK offers tight integration within the AWS ecosystem but may face challenges in multi-cloud deployments despite benefiting AWS users through streamlined service integration.

Pricing and ROI: Databricks employs flexible pricing models catering to diverse business needs, which can result in high ROI from data insights. Amazon MSK's pay-as-you-go pricing appeals to existing AWS customers, with cost efficiency tied to data throughput, offering a budget-friendly option for streaming services. Both solutions offer competitive pricing, with Databricks potentially requiring higher initial investment but yielding substantial returns through efficient data strategies, whereas Amazon MSK provides an economical choice within the AWS ecosystem.

To learn more, read our detailed Amazon MSK vs. Databricks Report (Updated: December 2025).

Amazon MSK vs. Databricks

December 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:

ROI

Sentiment score

4.1

Amazon MSK saves time and money, promotes innovation with flexible pricing, yet some users find costs hard to justify.

Sentiment score

6.4

Users experience mixed returns with Databricks, noting cost efficiency and scalability but facing challenges with measuring monetary gains.

No quotes available

For more quotes and insights, download the Amazon MSK report

For a lot of different tasks, including machine learning, it is a nice solution.

For more quotes and insights, download the Databricks report

Senior Data Engineer at a logistics company with 51-200 employees

When it comes to big data processing, I prefer Databricks over other solutions.

IshwarSukheja

Head CEO at bizmetric

Customer Service

Sentiment score

6.2

Amazon MSK support varies; some praise its effectiveness, while others note average service and seek external assistance.

Sentiment score

7.0

Databricks customer service is praised for prompt, professional support, though some report delays; documentation helps many users.

They can manage most of our queries, and for what they cannot manage, they guide us through the process of finding out.

Co-Founder & CTO at Photios AI

Amazon's support is excellent.

For more quotes and insights, download the Amazon MSK report

CTO at Atulya Abhinav Tech Private Limited

Whenever we reach out, they respond promptly.

Senior Data Engineer at a logistics company with 51-200 employees

As of now, we are raising issues and they are providing solutions without any problems.

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Data Platform Architect at KELLANOVA

I rate the technical support as fine because they have levels of technical support available, especially partners who get really good support from Databricks on new features.

Lax Kas

Data Engineer at CRAFT Tech

Scalability Issues

Sentiment score

6.0

Amazon MSK is viewed as scalable, manageable, appealing to various environments, but may require manual scaling adjustments.

Sentiment score

7.4

Databricks is praised for its scalability, elasticity, and auto-scaling, providing high performance and flexibility across industries.

The functionality for scaling comes out of the box and is very effective.

CTO at Atulya Abhinav Tech Private Limited

As a B2B enterprise client, our clientele consists of large ticket clients but low amounts of users.

For more quotes and insights, download the Amazon MSK report

Co-Founder & CTO at Photios AI

The sky's the limit with Databricks.

SimonRobinson

Governance And Engagement Lead

The patches have sometimes caused issues leading to our jobs being paused for about six hours.

Senior Data Engineer at a logistics company with 51-200 employees

Databricks is an easily scalable platform.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

Stability Issues

Sentiment score

7.3

Amazon MSK is stable with high ratings; minor issues are unrelated to MSK, maintaining success rates of 91% under load.

Sentiment score

7.6

Databricks is highly rated for reliability and efficiency, with minor issues quickly resolved, boasting strong user stability scores.

It doesn't require any maintenance on my end yet, as I haven't had any issues.

Mauro Velasco Sarmiento

Senior Software Engineer at a consultancy with 201-500 employees

For more quotes and insights, download the Amazon MSK report

They release patches that sometimes break our code.

Senior Data Engineer at a logistics company with 51-200 employees

Although it is too early to definitively state the platform's stability, we have not encountered any issues so far.

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Data Platform Architect at KELLANOVA

Databricks is definitely a very stable product and reliable.

AvivCohen

Data Engineer at a tech vendor with 1,001-5,000 employees

Room For Improvement

Amazon MSK struggles with integration, configuration complexities, high costs, and operational challenges compared to services like Kinesis.

Databricks needs better visualization, integration, clearer errors, UI enhancements, wider platform support, and improved documentation and usability.

The increase in cloud costs by 50% to 60% does not justify the savings.

CTO at Atulya Abhinav Tech Private Limited

The only issue with Amazon MSK that we are facing is the configurations.

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Co-Founder & CTO at Photios AI

I had to remove and drop all the clusters and recreate them again, which is complicated in a production environment.

Mauro Velasco Sarmiento

Senior Software Engineer at a consultancy with 201-500 employees

Adjusting features like worker nodes and node utilization during cluster creation could mitigate these failures.

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

We prefer using a small to mid-sized cluster for many jobs to keep costs low, but this sometimes doesn't support our operations properly.

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Senior Data Engineer at a logistics company with 51-200 employees

We use MLflow for managing MLOps, however, further improvement would be beneficial, especially for large language models and related tools.

Rama Subba Reddy Thavva

Solution Architect at Mercedes-Benz AG

Setup Cost

Amazon MSK is competitively priced with variable costs, appealing to enterprise users but potentially expensive for some.

Databricks' pricing varies widely based on usage and data volume, making it cost-effective yet potentially expensive for large-scale use.

Once we started using Kafka, our cloud costs rose by 50% to 60%.

CTO at Atulya Abhinav Tech Private Limited

We use Kafka M5 Large instance, and depending on the instances, that is the cost we have, along with storage cost and data transfer costs.

For more quotes and insights, download the Amazon MSK report

Co-Founder & CTO at Photios AI

It is not a cheap solution.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

I believe that in terms of credits for Databricks, we're spending between £15,000 and £20,000 a month.

SimonRobinson

Governance And Engagement Lead

Valuable Features

Amazon MSK integrates AWS services, offering cost-effective, automated scaling, ease of use, real-time analytics, encryption, and event sourcing.

Databricks excels in ease of use, scalability, integration, and data governance, enhancing productivity and collaboration for data engineering.

The scalability and usability are quite remarkable.

CTO at Atulya Abhinav Tech Private Limited

The best features of Amazon MSK are the real-time analytics that are excellent.

For more quotes and insights, download the Amazon MSK report

Co-Founder & CTO at Photios AI

Amazon MSK is basically Kafka in the cloud, and when you need to create a cluster of Kafka brokers, Amazon MSK helps with that by automatically creating all the brokers according to the configuration you provide.

Mauro Velasco Sarmiento

Senior Software Engineer at a consultancy with 201-500 employees

Databricks' capability to process data in parallel enhances data processing speed.

ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

The platform allows us to leverage cloud advantages effectively, enhancing our AI and ML projects.

For more quotes and insights, download the Databricks report

Data Platform Architect at KELLANOVA

The Unity Catalog is for data governance, and the Delta Lake is to build the lakehouse.

Lax Kas

Data Engineer at CRAFT Tech

Categories and Ranking

Amazon MSK

Ranking in Streaming Analytics

6th

Average Rating

7.2

Reviews Sentiment

6.5

Number of Reviews

Ranking in other categories

No ranking in other categories

Databricks

Ranking in Streaming Analytics

1st

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Warehouse (9th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th)

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Amazon MSK is 5.1%, down from 8.4% compared to the previous year. The mindshare of Databricks is 10.0%, down from 13.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics Market Share Distribution
Product	Market Share (%)
Databricks	10.0%
Amazon MSK	5.1%
Other	84.9%

Streaming Analytics

Featured Reviews

Improved data streaming and integration challenges prompt search for alternatives

Co-Founder & CTO at Photios AI

The integration capabilities of Amazon MSK are not very flexible. If you have your own self-managed Kafka, that helps significantly because you can set up configurations. We are considering self-managed Kafka since our product is only one year old. The Kafka integrations are fine, but the configurations are an issue. The only issue with Amazon MSK that we are facing is the configurations. There are preset configurations and limited configurations that we can set for our unique use case. The product could improve by allowing us to set different configurations. I would also like to see Amazon MSK improve in the area of connectors. We are considering Confluent Cloud because they have many more connectors. They have KSQL DB and governance features. It is slightly costlier, but Confluent offers more flexibility with their connectors.

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SimonRobinson

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.

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Top Industries

By visitors reading reviews

Financial Services Firm

22%

Computer Software Company

12%

Manufacturing Company

Construction Company

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	4
Midsize Enterprise	7
Large Enterprise	4

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

Questions from the Community

What do you like most about Amazon MSK?

Amazon MSK has significantly improved our organization by building seamless integration between systems.

What needs improvement with Amazon MSK?

What is your primary use case for Amazon MSK?

We are recently working with Amazon MSK at Fortis, where we have multiple dashboards in our revenue intelligence platform. We are streaming data from different apps into those dashboards. The data ...

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...

Azure Stream Analytics vs Amazon MSK

Comparisons

Compared 24% of the time

Apache Flink vs Amazon MSK

Compared 14% of the time

Confluent vs Amazon MSK

Compared 11% of the time

Aiven Platform vs Amazon MSK

Compared 9% of the time

Apache Spark Streaming vs Amazon MSK

Compared 3% of the time

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Dataiku vs Databricks

Compared 6% of the time

Microsoft Power BI vs Databricks

Compared 6% of the time

Informatica PowerCenter vs Databricks

Compared 5% of the time

Dremio vs Databricks

Compared 4% of the time

Tableau Enterprise vs Databricks

Compared 3% of the time

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Product Reports

Download Amazon MSK product report

Amazon MSK

January 2026

Download Databricks product report

January 2026

Also Known As

Amazon Managed Streaming for Apache Kafka

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Overview

Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.

Amazon Web Services (AWS)

Databricks offers a scalable, versatile platform that integrates seamlessly with Spark and multiple languages, supporting data engineering, machine learning, and analytics in a unified environment.

Databricks stands out for its scalability, ease of use, and powerful integration with Spark, multiple languages, and leading cloud services like Azure and AWS. It provides tools such as the Notebook for collaboration, Delta Lake for efficient data management, and Unity Catalog for data governance. While enhancing data engineering and machine learning workflows, it faces challenges in visualization and third-party integration, with pricing and user interface navigation being common concerns. Despite needing improvements in connectivity and documentation, it remains popular for tasks like real-time processing and data pipeline management.

What features make Databricks unique?

Notebook: Enables collaborative work among team members.
Delta Lake: Optimizes data management operations.
Unity Catalog: Provides governance over data assets.
Cloud Integration: Seamlessly connects with major cloud platforms.

What benefits can users expect from Databricks?

Versatility: Supports diverse applications in data science and engineering.
Performance: Delivers efficient handling of large-scale analytics tasks.
Collaboration: Enhances teamwork in data projects.
Unified Environment: Centralizes machine learning and analytics activities.

In the tech industry, Databricks empowers teams to perform comprehensive data analytics, enabling them to conduct extensive ETL operations, run predictive modeling, and prepare data for SparkML. In retail, it supports real-time data processing and batch streaming, aiding in better decision-making. Enterprises across sectors leverage its capabilities for creating secure APIs and managing data lakes effectively.

Sample Customers

Expedia, Intuit, Royal Dutch Shell, Brooks Brothers

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware