Confluent vs Databricks comparison

Confluent and Databricks are both solutions in the Streaming Analytics category. Confluent is ranked #4 with an average rating of 8.3, while Databricks is ranked #1 with an average rating of 8.3. Confluent holds a 8.5% mindshare in SA, compared to Databricks’s 14.1% mindshare. Additionally, 95% of Confluent users are willing to recommend the solution, compared to 96% of Databricks users who would recommend it.

Confluent

Read 23 Confluent reviews

5,755 Views
4,333 Comparison Views

95% willing to recommend

Databricks

Read 88 Databricks reviews

6,640 Views
4,466 Comparison Views

96% willing to recommend

Confluent

Databricks

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Executive SummaryUpdated on Dec 17, 2024

Databricks and Confluent are significant players in data analytics and real-time data streaming. Databricks holds an advantage in data manipulation and machine learning capabilities, while Confluent excels in scalability and real-time data streaming integration.

Features: Databricks offers large-scale analytics with built-in machine learning capabilities and Delta Lake for data engineering, alongside seamless integration with multiple programming languages. Confluent, based on Kafka, provides robust real-time data streaming, easy system integration, scalability, and adaptability, making it a strong competitor.

Room for Improvement: Databricks could improve in visualization capabilities, integration with third-party tools like Power BI, and offer better cost efficiency. Confluent could focus on developing intuitive plugins, broadening its range of managed connectors, and enhancing its user interfaces for improved user experiences and metric systems.

Ease of Deployment and Customer Service: Databricks is noted for its ease of deployment across cloud environments and good customer support, although some users experience delays. Confluent provides robust cloud support, positive customer service feedback, and detailed documentation that simplifies deployment.

Pricing and ROI: Databricks uses a pay-per-use model, which can be expensive, but it justifies the cost with its comprehensive toolset, showing ROI in batch processing environments. Confluent's pricing is competitive relative to its streaming capabilities, providing value through configurability and scalability that translates into reasonable ROI for robust data streaming needs.

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

Buyer's Guide

Confluent vs. Databricks

January 2025

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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

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

Ranking in other categories

Cloud Data Warehouse (7th), Data Science Platforms (1st)

Mindshare comparison

As of February 2025, in the Streaming Analytics category, the mindshare of Confluent is 8.5%, down from 11.6% compared to the previous year. The mindshare of Databricks is 14.1%, up from 9.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Yantao Zhao

Software Integration Engineer at Thales

Great tool for sharing knowledge, internal communication and allows for real-time collaboration on pages

Confluence is easy to use and modify. However, sometimes there are too many pages. We have to reorganize the folder or parent account. Since everyone can create a page, the same knowledge might be created in multiple places by different people. This leads to redundancy and makes it difficult to find information. It's not centralized. So it could be more user-friendly and centralized. A way to reduce redundancy would be helpful. It's very easy to use, so everyone can create knowledge. But it would be good to synchronize and organize that information a bit better. Another improvement would be in Confluence search. You can search for keywords, but it's not like AI, not even ChatGPT or OpenAI. It would be nice to get more relevant or organized answers. If you're outside the company, you just get some titles containing the keyword you input. But if Confluence were like a database, you could input something and get a well-organized search offering from multiple pages.

Read full review

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

Quotes from Members

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

Pros

"Their tech support is amazing; they are very good, both on and off-site."

"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 solution can handle a high volume of data because it works and scales well."

"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."

"We mostly use the solution's message queues and event-driven architecture."

"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."

"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."

"The most valuable is its capability to enhance the documentation process, particularly when creating software documentation."

More Confluent pros

"The setup is quite easy."

"Databricks helps crunch petabytes of data in a very short period of time."

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

"The main features of the solution are efficiency."

"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."

"Databricks' Lakehouse architecture has been most useful for us. The data governance has been absolutely efficient in between other kinds of solutions."

"Can cut across the entire ecosystem of open source technology to give an extra level of getting the transformatory process of the data."

"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."

More Databricks pros

Cons

"It would help if the knowledge based documents in the support portal could be available for public use as well."

"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."

"It could have more themes. They should also have more reporting-oriented plugins as well. It would be great to have free custom reports that can be dispatched directly from Jira."

"There is no local support team in Saudi Arabia."

"We continuously face issues, such as Kafka being down and slow responses from the support team."

"In Confluent, there could be a few more VPN options."

"It requires some application specific connectors which are lacking. This needs to be added."

"Confluent has a good monitoring tool, but it's not customizable."

More Confluent cons

"We often use a single cluster to ingest Databricks, which Databricks doesn't recommend. They suggest using a no-cluster solution like job clusters. This can be overwhelming for us because we started smaller."

"Anyone who doesn't know SQL may find the product difficult to work with."

"It would be better if it were faster. It can be slow, and it can be super fast for big data. But for small data, sometimes there is a sub-second response, which can be considered slow. In the next release, I would like to have automatic creation of APIs because they don't have it at the moment, and I spend a lot of time building them."

"Performance could be improved."

"The interface of Databricks could be easier to use when compared to other solutions. It is not easy for non-data scientists. The user interface is important before we had to write code manually and as solutions move to "No code AI" it is critical that the interface is very good."

"Pricing is one of the things that could be improved."

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

"Databricks' technical support takes a while to respond and could be improved."

More Databricks cons

Pricing and Cost Advice

"Confluent is an expensive solution as we went for a three contract and it was very costly for us."

"It comes with a high cost."

"The solution is cheaper than other products."

"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."

"Confluent has a yearly license, which is a bit high because it's on a per-user basis."

"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."

"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."

More Confluent pricing and cost advice

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

"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."

"The billing of Databricks can be difficult and should improve."

"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."

"There are different versions."

"I would rate Databricks' pricing seven out of ten."

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

"The solution requires a subscription."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

19%

Computer Software Company

17%

Manufacturing Company

Insurance Company

Financial Services Firm

17%

Computer Software Company

11%

Manufacturing Company

Healthcare Company

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...

See all answers

What is your experience regarding pricing and costs for Confluent?

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 maintenanc...

See all answers

What needs improvement with Confluent?

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 c...

See all answers

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

Comparisons

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Compared 16% of the time

Amazon MSK vs Confluent

Compared 12% of the time

Fivetran vs Confluent

Compared 5% of the time

AWS Glue vs Confluent

Compared 4% of the time

Palantir Foundry vs Confluent

Compared 4% of the time

More Confluent Competitors

Dataiku vs Databricks

Compared 11% of the time

Dremio vs Databricks

Compared 8% of the time

Microsoft Power BI vs Databricks

Compared 8% of the time

Informatica PowerCenter vs Databricks

Compared 8% of the time

Amazon SageMaker vs Databricks

Compared 7% of the time

More Databricks Competitors

Product Reports

Buyer's Guide

Confluent

February 2025

Download Confluent product report

Buyer's Guide

Databricks

February 2025

Download Databricks product report

Also Known As

No data available

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Overview

Confluent is an enterprise-ready, full-scale streaming platform that enhances Apache Kafka.

Confluent has integrated cutting-edge features that are designed to enhance these tasks:

Speed up application development and connectivity
Enable transformations through stream processing
Streamline business operations at scale
Adhere to strict architectural standards

Confluent is a more complete distribution of Kafka in that it enhances the integration possibilities of Kafka by introducing tools for managing and optimizing Kafka clusters while providing methods for making sure the streams are secure. Confluent supports publish-and-subscribe as well as the storing and processing of data within the streams. Kafka is easier to operate and build thanks to Confluent.

Confluent's software is available in three different varieties:

A free, open-source streaming platform that makes it simple to start using real-time data streams
An enterprise-grade version of the product with more administrative, ops, and monitoring tools
A premium cloud-based version.

Confluent Advantage Features

Confluent has many valuable key features. Some of the most useful ones include:

Multi-language
- Clients: C++, Python, Go, and .NET
- REST proxy: Can connect to Kafka from any connected network device
- Admin REST APIs: RESTful interface for performing administrator operations

Pre-built ecosystem
- Connectors: More than 100 supported connectors, including S3, Elastic, HDFS, JDBC
- MQTT proxy: Gain access to Kafka from MQTT gateways and devices
- Schema registry: Centralized database to guarantee data compatibility

Streaming database
- ksqlDB: Materialized views and real-time stream processing

GUI management
- Control panel: GUI for scalable Kafka management and monitoring
- Health+: Smart alerts and cloud-based control centers

DevOps automation that is flexible
- Confluent for Kubernetes: Complete API to deploy on Kubernetes
- Automated Ansible deployment on non-containerized environments

Dynamic performance
- Self-balancing clusters: Automated partition re-balancing across brokers in the cluster
- Tiered storage: Older Kafka data offloading to object storage with transparent access

Security that is enterprise-grade
- Role-based access control: Granular user/group access authorization
- Audit logs that are structured: Logs of user actions kept in dedicated Kafka topics
- Secret protection: Sensitive information is encrypted

Global resilience
- Linking clusters: A real-time, highly reliable, and consistent bridge across on-premises and cloud environments
- Multiple-region clusters: Single Kafka cluster with automated client failover distributed across multiple data centers
- Replicator: Asynchronous replication that is based on the Kafka Connect framework

Support
- Round the clock enterprise support from Kafka experts

Reviews from Real Users

Confluent stands out among its competitors for a number of reasons. Two major ones are its robust enterprise support and its open source option. PeerSpot users take note of the advantages of these features in their reviews:

Ravi B., a solutions architect at a tech services company, writes of the solution, “KSQL is a valuable feature, as is the Kafka Connect framework for connecting to the various source systems where you need not write the code. We get great support from Confluent because we're using the enterprise version and whenever there's a problem, they support us with fine-tuning and finding the root cause.”

Amit S., an IT consultant, notes, “The biggest benefit is that it is open source. You have the flexibility of opting or not opting for enterprise support, even though the tool itself is open source.” He adds, “The second benefit is it's very modern and built on Java and Scala. You can extend the features very well, and it doesn't take a lot of effort to do so.”

Confluent

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

Sample Customers

ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost

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

Buyer's Guide

Confluent vs. Databricks

January 2025

Free Report: Confluent vs. Databricks

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