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Apache Kafka Reviews

Vendor: Apache
4.1 out of 5
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What is Apache Kafka?

Apache Kafka is an open-source distributed streaming platform that serves as a central hub for handling real-time data streams. It allows efficient publishing, subscribing, and processing of data from various sources like applications, servers, and sensors.

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Apache Kafka is the #7 ranked solution in Streaming Analytics tools. PeerSpot users give Apache Kafka an average rating of 8.2 out of 10. Apache Kafka is most commonly compared to Databricks: Apache Kafka vs Databricks. Apache Kafka is popular among the large enterprise segment, accounting for 60% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a financial services firm, accounting for 22% of all views.
Buyer's Guide
Apache Kafka
January 2026
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Apache Kafka mindshare

As of January 2026, the mindshare of Apache Kafka in the Streaming Analytics category stands at 3.8%, up from 2.2% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Apache Kafka3.8%
Apache Flink12.3%
Databricks10.0%
Other73.9%
Streaming Analytics

PeerResearch reports based on Apache Kafka reviews

TypeTitleDate
CategoryStreaming AnalyticsJan 26, 2026Download
ProductReviews, tips, and advice from real usersJan 26, 2026Download
ComparisonApache Kafka vs DatabricksJan 26, 2026Download
ComparisonApache Kafka vs Amazon KinesisJan 26, 2026Download
ComparisonApache Kafka vs Azure Stream AnalyticsJan 26, 2026Download
Suggested products
TitleRatingMindshareRecommending
Databricks4.110.0%96%92 interviewsAdd to research
Confluent4.16.8%95%25 interviewsAdd to research
 
 
Key learnings from peers
Last updated Dec 28, 2025

Valuable Features

Apache Kafka's most valuable features include replication, partitioning, scalability, and integration with Apache Spark. It offers high throughput, reliability, and fault-tolerance for distributed processing. Users appreciate its ability to handle large-scale messaging, manage high data volumes, and ensure message retention. Its versatility allows real-time processing and message bus functionalities. Kafka Connect and APIs enhance its integration capabilities, making it suitable for diverse applications like event streaming and data analytics.
  • "Apache Kafka is a mature product and can handle a massive amount of data in real time for data consumption."
  • "Apache Kafka is particularly valuable for stream data processing, handling transactions, managing high levels of transactions, and orchestrating stream mode data."
  • "I appreciate that Apache Kafka is fast and secure thanks to implementing it with AWS, allowing me to secure it on a high level."

Room for Improvement

Apache Kafka requires improvements in areas like UI enhancement, stability, and a user-friendly admin interface. Many highlight the challenge of dependability on ZooKeeper and issues with documentation clarity. Some companies seek better integration with external tools, enhanced monitoring capabilities, and optimized latency. The complexity of configuration and management poses difficulties, while graphical interfaces and real-time processing enhancements are highly sought after. Compatibility with other systems and increased automation support would benefit users significantly.
  • "Scalability may cause issues in the product if my nodes are full with multiple sources and delivery is slowing down."
  • "The interface of Apache Kafka could be significantly better."
  • "For personal preferences, since we use Managed Kafka in AWS, I would appreciate having some kind of UI integrated into Apache Kafka for connecting to it because using code to connect it is basic, but we can use a UI."

ROI

Many report Apache Kafka delivering substantial return on investment, especially for high-value and large-scale projects, primarily through real-time capabilities and cost savings due to its open-source nature. Some observe significant insights and faster decision-making. Others mention efficiency in data management and ability to manage traffic effectively contributed positively to investment returns. However, in certain applications like specific use cases and when not deeply integrated, the returns haven't been noteworthy.

Pricing

Apache Kafka is predominantly valued for being open-source and free to use, eliminating direct software costs. Many enterprises opt for the cost-effective open-source version due to the absence of licensing fees. However, the platform's premium offerings, such as Confluent Cloud, can incur additional expenses, often requiring negotiation for enterprise-level support and services. Managed services or cloud-based setups introduce variable costs based on usage, yet are considered affordable by users seeking scalability and convenience.
  • "I was using the product's free version."
  • "Apache Kafka is an open-source solution."
  • "It's quite affordable considering the value it provides."

Popular Use Cases

Companies use Apache Kafka primarily for data integration, real-time data consumption, and as a message queue for microservices. They deploy it for connecting management systems, handling big data, event streaming, financial messaging, log aggregation, and IoT data processing. Kafka facilitates data transfer, analytics, fraud detection, and event-driven processes. Organizations implement it both on-premise and in cloud environments to manage high volumes of data, enriching and transforming it for real-time analytics and reporting.

Service and Support

Apache Kafka's customer support primarily relies on an active open-source community. Some use Confluent for enhanced professional service, noting notable guidance in development stages but express dissatisfaction with deployment support. Paid support from third-party providers like Confluent and HPE is an option. While many have not needed direct support, those who rate it find communication efficient but request more comprehensive documentation. Queries are generally resolved via community forums and specialized consulting companies.

Deployment

Most users describe Apache Kafka's initial setup as straightforward, especially when using Docker and documentation. Some found challenges with complex infrastructures and sharding large volumes. Those with experience or proper resources tend to have an easier setup process. Difficulties often arise with production environments, requiring more configuration and expertise. Utilizing tools like ZooKeeper or cloud solutions helps simplify installation processes. For some, setup complexity varies based on organizational requirements and infrastructure.

Scalability

Apache Kafka is widely recognized for its scalability across various implementations. Users report it excels in horizontal scaling, handling high volumes of data across numerous nodes. Challenges may arise in managing resources and configuring for specific setups, particularly on-premise. Many find it easy to add brokers and use cloud solutions for added flexibility. Its architecture allows effortless scaling, although scaling down and resource allocation may require attention. Overall, many rate its scalability highly.

Stability

Many users report that Apache Kafka is stable, handling massive data efficiently, even under high volumes. Some note occasional issues with configurations and APIs, but these seem infrequent. Stability may vary due to latency and resource challenges, and stability can depend on appropriate management and tuning. Users find the partitioning feature enhances system reliability during high data loads, and Kafka's replication factor helps mitigate data loss, making it reliable for enterprise use.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
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Review data by company size

By reviewers
Company SizeCount
Small Business26
Midsize Enterprise17
Large Enterprise35
By reviewers
By visitors reading reviews
Company SizeCount
Small Business161
Midsize Enterprise97
Large Enterprise386
By visitors reading reviews

Top industries

By visitors reading reviews
Financial Services Firm
22%
Computer Software Company
11%
Manufacturing Company
9%
Retailer
5%
Comms Service Provider
4%
Government
4%
Insurance Company
4%
University
4%
Healthcare Company
3%
Energy/Utilities Company
3%
Real Estate/Law Firm
3%
Outsourcing Company
3%
Educational Organization
3%
Transportation Company
2%
Performing Arts
2%
Construction Company
2%
Media Company
2%
Hospitality Company
1%
Legal Firm
1%
Aerospace/Defense Firm
1%
Pharma/Biotech Company
1%
Logistics Company
1%
Wholesaler/Distributor
1%
Consumer Goods Company
1%
Non Profit
1%
Recreational Facilities/Services Company
1%
Marketing Services Firm
1%
Museum Or Institution
1%

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Learn more about Apache Kafka

Kafka's core benefits include high scalability for big data pipelines, fault tolerance ensuring continuous operation despite node failures, low latency for real-time applications, and decoupling of data producers from consumers.

Key features include topics for organizing data streams, producers for publishing data, consumers for subscribing to data, brokers for managing clusters, and connectors for easy integration with various data sources.

Large organizations use Kafka for real-time analytics, log aggregation, fraud detection, IoT data processing, and facilitating communication between microservices.

Apache Kafka customers

Uber, Netflix, Activision, Spotify, Slack, Pinterest

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Product Categories

Product Categories
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Apache Kafka Reviews Summary
Author infoRatingReview Summary
Senior Manager at Timestamp, SA4.5I've used Apache Kafka since 2018 for high-volume stream data and transactions; it's improved greatly over time, though scaling and the interface need work. Setup is now simpler, and I rate it 9 out of 10 overall.
Works3.5In our Telco projects, Apache Kafka efficiently handled large volumes of streaming data, particularly for real-time customer airtime purchases. Although its usability could be enhanced, it outperformed RabbitMQ for our needs, despite no immediate ROI observed.
Solution Architect at Ascendion5.0I've used Apache Kafka for real-time data streaming and integration across systems, valuing its scalability, replication, and Kafka Connect. It's mature, easy to install, reliable in my experience, though long-term storage and scalability need attention.
Technology Leader at eTCaaS4.5I worked with Apache Kafka for financial and OTT platforms, primarily for data streaming. It's valuable for propagating data in motion but could improve performance, aiming for microseconds instead of milliseconds. No other solutions were considered and deployment is cloud-based.
DevOps Engineer4.0In our big project, Apache Kafka is essential for message exchange. I value its speed and security with AWS, though we could benefit from an integrated UI. Its scalability suits varying throughput needs, and I have observed some ROI.
Sr. Lead - Engineering at GlobalLogic4.5We primarily use Kafka for event streaming, valuing its scalability, language integration, and stability. While we've seen increased productivity, the UI could be improved for better user appeal. We haven't considered other streaming solutions.
Group Manager at a media company with 201-500 employees4.5In my experience with Apache Kafka, it is effective for real-time data streaming, notably benefiting fraud detection in the banking sector. However, improvements are needed in handling large data volumes, restart capabilities, and resource monitoring to enhance performance and integration.
Technical Director at NIDP4.5We use Apache Kafka for stage event-driven processes, valuing its real-time data processing and stability. Despite limited queue management capabilities, it offers cost-saving benefits over proprietary solutions without prior alternatives evaluated. Kafka facilitates smooth setup post-data center outages.