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 8.3, while Redpanda Data is ranked #16 with an average rating of 8.8. Databricks holds a 14.5% mindshare in SA, compared to Redpanda Data’s 1.0% 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 91 Databricks reviews

4,950 Views
3,220 Comparison Views

96% willing to recommend

Redpanda

Read 4 Redpanda reviews

249 Views
98 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: June 2025).

Buyer's Guide

Databricks vs. Redpanda

June 2025

Download the complete report

Helped 859,129 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 (8th), Data Science Platforms (1st)

Redpanda

Ranking in Streaming Analytics

16th

Average Rating

8.8

Reviews Sentiment

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of June 2025, in the Streaming Analytics category, the mindshare of Databricks is 14.5%, up from 10.8% compared to the previous year. The mindshare of Redpanda is 1.0%, up from 0.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

ShubhamSharma7

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

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.

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

"What I like about Databricks is that it's one of the most popular platforms that give access to folks who are trying not just to do exploratory work on the data but also go ahead and build advanced modeling and machine learning on top of that."

"We like that this solution can handle a wide variety and velocity of data engineering, either in batch mode or real-time."

"Databricks makes it really easy to use a number of technologies to do data analysis. In terms of languages, we can use Scala, Python, and SQL. Databricks enables you to run very large queries, at a massive scale, within really good timeframes."

"The most valuable feature is the Spark cluster which is very fast for heavy loads, big data processing and Pi Spark."

"The built-in optimization recommendations halved the speed of queries and allowed us to reach decision points and deliver insights very quickly."

"It's very simple to use Databricks Apache Spark."

"I like that Databricks is a unified platform that lets you do streaming and batch processing in the same place. You can do analytics, too. They have added something called Databricks SQL Analytics, allowing users to connect to the data lake to perform analytics. Databricks also will enable you to share your data securely. It integrates with your reporting system as well."

"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"

More Databricks pros

"The cost savings have been significant."

"The UI is modern."

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

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

Cons

"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"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."

"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."

"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."

"The initial setup is difficult."

"I would love an integration in my desktop IDE. For now, I have to code on their webpage."

"Databricks is an analytics platform. It should offer more data science. It should have more features for data scientists to work with."

More Databricks cons

"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."

"The version control mechanism must be improved."

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

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

Pricing and Cost Advice

"Databricks uses a price-per-use model, where you can use as much compute as you need."

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

"The price is okay. It's competitive."

"The cost is around $600,000 for 50 users."

"Price-wise, I would rate Databricks a three out of five."

"The pricing depends on the usage itself."

"The licensing costs of Databricks depend on how many licenses we need, depending on which Databricks provides a lot of discounts."

"We have only incurred the cost of our AWS cloud services. This is because during this period, Databricks provided us with an extended evaluation period, and we have not spent much money yet. We are just starting to incur costs this month, I will know more later on the full cost perspective."

More Databricks pricing and cost advice

"Redpanda is cheaper than its competitors."

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

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

859,129 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

No data available

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

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 11% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 7% of the time

Tableau vs Databricks

Compared 5% of the time

More Databricks Competitors

Amazon Kinesis vs Redpanda

Compared 61% of the time

Apache Pulsar vs Redpanda

Compared 39% of the time

More Redpanda Competitors

Product Reports

Buyer's Guide

Databricks

June 2025

Download Databricks product report

Buyer's Guide

Redpanda

June 2025

Download Redpanda product report

Also Known As

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

No data available

Overview

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

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

June 2025

Free Report: Databricks vs. Redpanda

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

DOWNLOAD NOW

859,129 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.