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Confluent vs Databricks comparison

 

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

Confluent
Ranking in Streaming Analytics
4th
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
23
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
88
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st)
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Confluent is 8.5%, down from 11.4% compared to the previous year. The mindshare of Databricks is 14.6%, up from 10.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Gustavo-Barbosa Dos Santos - PeerSpot reviewer
Has good technical support services and a valuable feature for real-time data streaming
Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance. It helps us understand the various requirements of multiple customers and validates the information for different versions. We can automate the tasks using Confluent Kafka. Thus, it guarantees us the data quality and maintains the integrity of message contracts.
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.

Quotes from Members

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

Pros

"Confluence's greatest asset is its user-friendly interface, coupled with its remarkable ability to seamlessly integrate with a vast range of other solutions."
"With Confluent Cloud we no longer need to handle the infrastructure and the plumbing, which is a concern for Confluent. The other advantage is that all portfolios have access to the data that is being shared."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"The design of the product is extremely well built and it is highly configurable."
"The solution can handle a high volume of data because it works and scales well."
"Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance."
"The client APIs are the most valuable feature."
"It is also good for knowledge base management."
"It's easy to increase performance as required."
"The most valuable feature is the ability to use SQL directly with Databricks."
"This solution offers a lake house data concept that we have found exciting. We are able to have a large amount of data in a data lake and can manage all relational activities."
"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."
"The initial setup phase of Databricks was good."
"Databricks is based on a Spark cluster and it is fast. Performance-wise, it is great."
"I like the ability to use workspaces with other colleagues because you can work together even without seeing the other team's job."
"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."
 

Cons

"It could have more integration with different platforms."
"The Schema Registry service could be improved. I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well."
"Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent."
"The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"They should remove Zookeeper because of security issues."
"There is no local support team in Saudi Arabia."
"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."
"Implementation of Databricks is still very code heavy."
"They release patches that sometimes break our code. These patches are supposed to fix issues, but sometimes they cause disruptions."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"The initial setup is difficult."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"Scalability is an area with certain shortcomings. The solution's scalability needs improvement."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Databricks would benefit from enhanced metrics and tighter integration with Azure's diagnostics."
 

Pricing and Cost Advice

"It comes with a high cost."
"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."
"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."
"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."
"You have to pay additional for one or two features."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"Databricks' cost could be improved."
"The cost is around $600,000 for 50 users."
"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."
"We only pay for the Azure compute behind the solution."
"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."
"We're charged on what the data throughput is and also what the compute time is."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"The solution is affordable."
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Computer Software Company
16%
Manufacturing Company
7%
Insurance Company
6%
Financial Services Firm
17%
Computer Software Company
10%
Manufacturing Company
9%
Healthcare Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Confluent?
I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...
What is your experience regarding pricing and costs for Confluent?
They charge a lot for scaling, which makes it expensive.
What needs improvement with Confluent?
I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team. The lack of easy access to the Confluent support team is also a...
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...
 

Comparisons

 

Also Known As

No data available
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
 

Overview

 

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Find out what your peers are saying about Confluent vs. Databricks and other solutions. Updated: April 2025.
848,716 professionals have used our research since 2012.