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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
6th
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
93
Ranking in other categories
Cloud Data Warehouse (4th), Data Science Platforms (1st), Data Management Platforms (DMP) (5th)
 

Mindshare comparison

As of May 2026, in the Streaming Analytics category, the mindshare of Confluent is 6.6%, down from 8.2% compared to the previous year. The mindshare of Databricks is 8.1%, down from 14.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics Mindshare Distribution
ProductMindshare (%)
Databricks8.1%
Confluent6.6%
Other85.3%
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

"Confluent is an amazing tool that is highly configurable, integrates very well with Jira, and lets you create nice documentation for various products while also supporting reporting and online content hosting."
"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."
"The solution can handle a high volume of data because it works and scales well."
"I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"We mostly use the solution's message queues and event-driven architecture."
"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."
"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 tools."
"Before I used Databricks it took me a long time to do some functions and now with Databricks I can do them much quicker."
"Databricks gives us the ability to build a lakehouse framework and do everything implicit to this type of database structure. We also like the ability to stream events. Databricks covers a broad spectrum, from reporting and machine learning to streaming events. It's important for us to have all these features in one platform."
"Easy to use and requires minimal coding and customizations."
"Databricks is a truly essential platform for data engineering needs, and I recommend it to anyone looking to advance in the data engineering field."
"Databricks is definitely a very stable product and reliable."
"The solution is easy to use and has a quick start-up time due to being on the cloud."
"The most valuable feature of Databricks is the notebook, data factory, and ease of use."
"By going through this solution, we were able to complete the processing of the data in half an hour."
 

Cons

"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"Confluent has fallen behind in being the tool of the industry. It's taking second place to things such as Word and SharePoint and other office tools that are more dynamic and flexible than Confluent."
"It would be great if the knowledge based documents in the support portal could be available for public use as well."
"It would help if the knowledge based documents in the support portal could be available for public use as well."
"There is a limitation when it comes to seamlessly importing Microsoft documents into Confluent pages, which can be inconvenient for users who frequently work with Microsoft Office tools and need to transition their content to Confluent."
"The pricing model should include the ability to pick features and be charged for them only."
"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."
"There is no local support team in Saudi Arabia."
"Anyone who doesn't know SQL may find the product difficult to work with."
"I would like it if Databricks adopted an interface more like R Studio."
"I believe that this product could be improved by becoming more user-friendly."
"The product cannot be integrated with a popular coding IDE."
"One area of improvement is the Databricks File System (DBFS), where command-line challenges arise when accessing files. Standardization of file paths on the system could help, as engineers sometimes struggle."
"Some of the error messages that we receive are too vague, saying things like "unknown exception", and these should be improved to make it easier for developers to debug problems."
"The tool should improve its integration with other products."
"The ability to customize our own pipelines would enhance the product, similar to what's possible using ML files in Microsoft Azure DevOps."
 

Pricing and Cost Advice

"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"Confluent is an expensive solution as we went for a three contract and it was very costly for us."
"Confluent is an expensive solution."
"Regarding pricing, I think Confluent is a premium product, but it's hard for me to say definitively if it's overly expensive. We're still trying to understand if the features and reduced maintenance complexity justify the cost, especially as we scale our platform use."
"The solution is cheaper than other products."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"It comes with a high cost."
"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."
"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."
"Databricks' cost could be improved."
"I would rate the tool’s pricing an eight out of ten."
"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."
"We pay as we go, so there isn't a fixed price. It's charged by the unit. I don't have any details detail about how they measure this, but it should be a mix between processing and quantity of data handled. We run a simulation based on our use cases, which gives us an estimate. We've been monitoring this, and the costs have met our expectations."
"The pricing depends on the usage itself."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
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Top Industries

By visitors reading reviews
Financial Services Firm
15%
Retailer
10%
Computer Software Company
10%
Manufacturing Company
5%
Financial Services Firm
18%
Manufacturing Company
9%
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 Enterprise16
By reviewers
Company SizeCount
Small Business27
Midsize Enterprise12
Large Enterprise56
 

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: April 2026.
893,221 professionals have used our research since 2012.