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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
9th
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
25
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
94
Ranking in other categories
Cloud Data Warehouse (4th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th)
 

Mindshare comparison

As of June 2026, in the Streaming Analytics category, the mindshare of Confluent is 6.6%, down from 8.3% compared to the previous year. The mindshare of Databricks is 7.9%, down from 14.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Databricks7.9%
Confluent6.6%
Other85.5%
Streaming Analytics
 

Featured Reviews

PavanManepalli - PeerSpot reviewer
AVP - Sr Middleware Messaging Integration Engineer at Wells Fargo
Has supported streaming use cases across data centers and simplifies fraud analytics with SQL-based processing
I recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about Confluent charging high fees while not offering features that match those of other tools. They need to improve in that direction by not only reducing costs but also providing better solutions for the problems customers face to avoid frustrations, whether through future enhancement requests or ensuring product stability. The cost should be worked on, and they should provide better solutions for customers. Solutions should focus on hierarchical topics; if a customer has different types of data and sources, they should be able to send them to the same place for analytics. Currently, Confluent requires everything to send to the same topic, which becomes very large and makes running analytics difficult. The hierarchy of topics should be improved. This part is available in MQ and other products such as Solace, but it is missing in Confluent, leading many in capital markets and trading to switch to Solace. In terms of stability, it is not the stability itself that needs improvement but rather the delivery semantics. Other products offer exactly-once delivery out of the box, whereas Confluent states it will offer this but lacks the knobs or levers for tuning configurations effectively. Confluent has hundreds of configurations that application teams must understand, which creates a gap. Users are often unaware of what values to set for better performance or to achieve exactly-once semantics, making it difficult to navigate through them. Delivery semantics also need to be worked on.
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.

Quotes from Members

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

Pros

"We primarily use Confluent for service desk and task management, and it is also good for knowledge base management."
"The design of the product is extremely well built and it is highly configurable."
"We ensure seamless management of Kafka through Confluent, allowing all of our Kafka activities to be handled by a third party."
"The documentation process is fast with the tool."
"The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka."
"The most valuable feature of Confluent is the wide range of features provided. They're leading the market in this category."
"The solution can handle a high volume of data because it works and scales well."
"Confluent facilitates the messaging tasks with Kafka, streamlining our processes effectively."
"Databricks covers end-to-end data analytics workflow in one platform, this is the best feature of the solution."
"Our company makes comprehensive use of the solution to consolidate data and do a certain amount of reporting and analytics."
"Databricks is a robust solution for big data processing, offering flexibility and powerful features."
"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 allowed us to go from non-existent insights (because the datasets were just too large) to immediate and rich insights once the datasets were ingested into our PySpark notebooks."
"One of the newest features brought into this solution provides you with a way to solve, deploy, and train models using the platform itself, or it can connect to your Azure Machine Learning in order to train, deploy, and productionalize some of the machine learning models."
"Compared to other companies, they offer great support to their clients."
 

Cons

"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"It could have more themes. The themes in the version I'm using are very limited; they offer two to three themes."
"Confluent has a good monitoring tool, but it's not customizable."
"Confluent's price needs improvement."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"It could have more integration with different platforms."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"The pricing was high for our needs. We should not have to pay for features we do not use."
"Would be helpful to have additional licensing options."
"When I used the support, I had communication problems because of the language barrier with the agent. The accent was difficult to understand."
"Performance could be improved."
"I would love an integration in my desktop IDE. For now, I have to code on their webpage."
"The initial setup of Databricks could be complex."
"We'd like a more visual dashboard for analysis It needs better UI."
"Can be improved by including drag-and-drop features."
"The integration of data could be a bit better."
 

Pricing and Cost Advice

"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."
"The solution is cheaper than other products."
"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."
"It comes with a high cost."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"Confluent is an expensive solution."
"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."
"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."
"Price-wise, I would rate Databricks a three out of five."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"There are different versions."
"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."
"The solution is based on a licensing model."
"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."
"Databricks' cost could be improved."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
Retailer
11%
Computer Software Company
8%
Manufacturing Company
6%
Financial Services Firm
18%
Manufacturing Company
10%
Computer Software Company
7%
Healthcare Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise4
Large Enterprise17
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise57
 

Questions from the Community

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 recommend that Confluent should improve its solution to keep up with competitors in the market, such as Solace and other upcoming tools such as NATS. Recently, there has been a lot of buzz about ...
What is your primary use case for Confluent?
The main use cases for Confluent are log aggregation and streaming. I'm familiar with Confluent stream processing with KSQL. KSQL helps in terms of data analytics strategies because if we are the d...
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: June 2026.
900,644 professionals have used our research since 2012.