Databricks vs Redpanda comparison

Databricks and Redpanda Data are both solutions in the Streaming Analytics category. Databricks is ranked #1 with an average rating of 8.4, while Redpanda Data is ranked #18 with an average rating of 8.8. Databricks holds a 10.0% mindshare in SA, compared to Redpanda Data’s 1.6% mindshare. Additionally, 96% of Databricks users are willing to recommend the solution, compared to 100% of Redpanda Data users who would recommend it.

Databricks

Read 92 Databricks reviews

18,651 Views
3,357 Comparison Views

96% willing to recommend

Redpanda

Read 4 Redpanda reviews

523 Views
507 Comparison Views

100% willing to recommend

Databricks

Redpanda

Comparison Buyer's Guide

Download the report

Executive SummaryUpdated on Dec 17, 2024

Databricks and Redpanda compete in the analytics and data streaming categories. Databricks seems to have the upper hand in big data capabilities and machine learning support, while Redpanda leads in cost-effectiveness and performance efficiency.

Features: Databricks offers seamless cluster management, an integration of Spark, and programming support for SQL and Python. It emphasizes big data capabilities, collaborative features, and scalability. Redpanda focuses on performance with high-speed data streaming built on C++, making it efficient and adaptable. It distinguishes itself with cost-effectiveness and simplicity.

Room for Improvement: Databricks users report vague error messages and limited online information, particularly in cost visibility and integration with popular BI tools. Redpanda can improve its documentation, especially for self-hosting scenarios, and refine its command-line tools for better data insights.

Ease of Deployment and Customer Service: Databricks offers deployment across public, private, and hybrid clouds with a reputable technical support team, though it sometimes faces delays and language barriers. Redpanda is centered on on-premises deployment, indicating less flexibility in cloud dynamics but benefits from a simpler setup. Both platforms need to enhance documentation and deployment guidance.

Pricing and ROI: Databricks is often seen as expensive, with users favoring a pay-as-you-go model, although it delivers positive ROI in reducing traditional RDBMS costs. Redpanda stands out for affordability, being cheaper than Kafka alternatives, and is praised for its free versions, offering high cost-effectiveness.

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

Buyer's Guide

Databricks vs. Redpanda

December 2025

Download the complete report

Helped 880,435 peers since 2012

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

Ranking in other categories

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

Redpanda

Ranking in Streaming Analytics

18th

Average Rating

9.2

Reviews Sentiment

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of January 2026, in the Streaming Analytics category, the mindshare of Databricks is 10.0%, down from 13.8% compared to the previous year. The mindshare of Redpanda is 1.6%, up from 0.4% 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%
Redpanda	1.6%
Other	88.4%

Streaming Analytics

Featured Reviews

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.

Read full review

ArpitShah

Software Analyst at CLSA

Affordable, easy to deploy, and it is easy to find things on the user interface

We use the libraries in the different programming languages. We use the message format in Avro, convert the data in the format, and pass it on. We have contacted the sales team about the solution. So far, the product fulfills our requirements. We get lots of data. The data flows through Kafka to Redpanda. Then it goes to a database. If our infrastructure goes down for a week, we will not lose data. It is an advantage of Redpanda. I recommend the product to others. We might choose a different solution if we find something cheaper. We used Redpanda because we did not want to self-host our software. Redpanda is a piece of infrastructure. There is not much of a learning curve. Overall, I rate the tool an eight out of ten.

Read full review

Quotes from Members

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

Pros

"I think Databricks is very good at facilitating AI and machine learning projects; they implement AI and machine learning models very well, and clients can run their models on Databricks."

"The technical support is good."

"The most valuable feature of Databricks is the notebook, data factory, and ease of use."

"It's great technology."

"The most valuable aspect of the solution is its notebook. It's quite convenient to use, both terms of the research and the development and also the final deployment, I can just declare the spark jobs by the load tables. It's quite convenient."

"Databricks is a scalable solution. It is the largest advantage of the solution."

"Databricks is definitely a very stable product and reliable."

"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."

More Databricks pros

"I tested it with ten-plus nodes, and it's highly scalable."

"The UI is modern."

"The cost savings have been significant."

"What makes Redpanda superior is its performance since it's written in C++. C++ is pretty much the standard for high-performance applications."

Cons

"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."

"Databricks requires writing code in Python or SQL, so if you're a good programmer then you can use Databricks."

"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."

"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."

"It would be very helpful if Databricks could integrate with platforms in addition to Azure."

"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."

"The solution could be improved by adding a feature that would make it more user-friendly for our team. The feature is simple, but it would be useful. Currently, our team is more familiar with the language R, but Databricks requires the use of Jupyter Notebooks which primarily supports Python. We have tried using RStudio, but it is not a fully integrated solution. To fully utilize Databricks, we have to use the Jupyter interface. One feature that would make it easier for our team to adopt the Jupyter interface would be the ability to select a specific variable or line of code and execute it within a cell. This feature is available in other Jupyter Notebooks outside of Databricks and in our own IDE, but it is not currently available within Databricks. If this feature were added, it would make the transition to using Databricks much smoother for our team."

"The query plan is not easy with Databrick's job level. If I want to tune any of the code, it is not easily available in the blogs as well."

More Databricks cons

"When it comes to self-hosting, their documentation could be improved."

"The command-line tools need to be improved. To quickly check the status of the topics and all."

"The version control mechanism must be improved."

"Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good."

Pricing and Cost Advice

"Databricks are not costly when compared with other solutions' prices."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"There are different versions."

"Whenever we want to find the actual costing, we have to send an email to Databricks, so having the information available on the internet would be helpful."

"We implement this solution on behalf of our customers who have their own Azure subscription and they pay for Databricks themselves. The pricing is more expensive if you have large volumes of data."

"The solution is affordable."

"The price of Databricks is reasonable compared to other solutions."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

More Databricks pricing and cost advice

"It's free. Everybody can use it, only support is paid."

"Redpanda is cheaper than its competitors."

See which vendors are best for you

Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.

See recommendations

880,435 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

18%

Manufacturing Company

Computer Software Company

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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

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 ...

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 designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Redpanda?

Redpanda is actually a commercial platform, but they do provide free versions as well. I've been working only with the free versions.

See all answers

What needs improvement with Redpanda?

Recently, for the documentation, they've built their own AI chatbot, which is focused on giving you answers based on their documentation. While using that, I did not find it to be very good. Maybe ...

See all answers

What is your primary use case for Redpanda?

I have worked with Redpanda for the past two to three months. Mainly in the tech industry or software industry, there's a huge rise of streaming data. Redpanda serves as a very reliable and fast me...

See all answers

Comparisons

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

More Databricks Competitors

Amazon Kinesis vs Redpanda

Compared 45% of the time

Apache Pulsar vs Redpanda

Compared 28% of the time

StreamNative vs Redpanda

Compared 15% of the time

PubSub+ Platform vs Redpanda

Compared 12% of the time

More Redpanda Competitors

Product Reports

Buyer's Guide

Databricks

January 2026

Download Databricks product report

Buyer's Guide

Redpanda

December 2025

Download Redpanda product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

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.

Databricks

Redpanda offers a modern, intuitive interface with efficient resource usage, seamlessly integrating with Kafka, and enhancing performance through fast operations and reliable support. Organizations benefit from its memory efficiency and high performance for demanding data workloads.

Built on a C++ foundation, Redpanda integrates easily with Kafka clients and stands out for fast operations, simplified Docker setup, and effective metrics monitoring. Performance is enhanced by memory efficiency and high throughput capabilities. The community provides robust support, and clear documentation aids the adoption process. However, improvements could be made in version control, command-line tools, and documentation, particularly in areas such as automation file management and chatbot documentation assistance. Redpanda is widely utilized in data streaming and normalization, efficiently handling large telemetry data volumes with minimal latency, essential for building asynchronous applications across microservices and monitoring systems.

What are the most important features of Redpanda?

Modern UI: Provides an intuitive interface for ease of use.
Efficient Resource Usage: Built on C++ for performance optimization.
Seamless Integration: Works well with Kafka clients for smooth operations.
Simplified Setup: Docker templates facilitate easy installation.
Built-in Metrics Exporters: Enhance monitoring and visibility.
High Performance: Ensures memory efficiency and quick data processing.

What benefits and ROI can users expect?

Fast Operations: Accelerates data processing for efficient workflows.
Reliable Support: Strong community aids troubleshooting and development.
Clear Documentation: Helps users quickly onboard and manage Redpanda.
Low Latency: Critical for applications requiring quick response times.
Sub-second Response: Supports demanding performance and latency needs.

Redpanda is commonly implemented in tech and software industries to streamline data streaming and normalization processes, handling high telemetry data volumes effectively. Its capacity for sub-second response times makes it crucial for companies developing asynchronous applications, especially in microservices and monitoring systems.

Redpanda Data

Sample Customers

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

Information Not Available

Buyer's Guide

Databricks vs. Redpanda

December 2025

Free Report: Databricks vs. Redpanda

Find out what your peers are saying about Databricks vs. Redpanda and other solutions. Updated: December 2025.

DOWNLOAD NOW

880,435 professionals have used our research since 2012.

See our Databricks vs. Redpanda report.

See our list of best Streaming Analytics vendors.

We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.