Overview
What is Apache Kafka?
Apache Kafka is an open-source stream processing platform developed by the Apache Software Foundation written in Scala and Java. The Kafka event streaming platform is used by thousands of companies for high-performance data pipelines, streaming analytics, data integration, and mission-critical…
Apache Kafka - Default Choice For Large Scale Messaging
Apache Kafka - FTW
A Deep Dive into the Power and Potential of Apache Kafka
Kafka for tracking changes
Confluent Kafka for messaging.
Kafka: Best Streaming Platform on the Market
Apache Kafka is awesome! Tricky sometimes, but we love it!
Kafka events; helping your company work with data
Apache Kafka - a must have tool for distributed toolkit
Kafka is an excellent tool for data integration!
Apache Kafka for your Data solutions
Excellent tech to manage short messages with high frequency
Apache Kafka: Where messaging meets storage
Apache Kafka open source stream processing software
Apache Kafka for large scale message ingestion
Reviewer Pros & Cons
Product Details
- About
- Tech Details
What is Apache Kafka?
Apache Kafka Technical Details
Operating Systems | Unspecified |
---|---|
Mobile Application | No |
Comparisons
Compare with
Reviews and Ratings
(127)Community Insights
- Business Problems Solved
- Pros
- Cons
- Recommendations
Apache Kafka is a widely-used platform that has proven to be invaluable in various industries and applications. It is relied upon by organizations to have real-time communication and keep order information up-to-date. This is particularly useful for organizations that need to process large volumes of data, such as those in the cybersecurity industry. Apache Kafka is also considered the go-to tool for event streaming, generating events and notifying relevant applications for consumption. Additionally, it is used in both first-party and third-party components of applications to address data proliferation and enable efficient notifications.
Another key use case for Apache Kafka is replacing classical messaging software within organizations, becoming the new standard for messaging. This powerful streaming framework plays a crucial role as a queuing mechanism for records in various pipelines, providing a simple yet efficient system for queuing and maintaining records. Moreover, Apache Kafka excels at storing and processing records in dedicated servers, supporting high data loads and offering the ability to replay consumed data. This makes it ideal for buffering incoming records during traffic spikes or in case of data infrastructure failures.
Furthermore, Apache Kafka finds its purpose in driving real-time monitoring by sending log information to feed other applications. Its ability to scale and manage common errors in messaging allows organizations to handle large quantities of messages per second without compromising performance. Another notable use case involves Apache Kafka acting as an efficient stream/message ingestion engine for customer-facing applications, enabling internal analytics and real-time decision-making.
Additionally, Apache Kafka integrates seamlessly with big data technologies like Spark, making it a valuable addition to big data ecosystems. Organizations have successfully replaced legacy messaging solutions with Apache Kafka, thanks to its ability to serve as a messaging and data-streaming pipeline solution. It enables modern streaming API-based applications while ensuring high availability and clustering as a message broker between client-facing applications.
Moreover, Apache Kafka serves as an ingress and egress queue for big data systems, facilitating data storage and retrieval processes. It also acts as a reliable queue for frontend applications to retrieve data and analytics from MapR and HortonWorks. With over five years of being utilized in data pipelines, Apache Kafka has consistently demonstrated excellent performance and reliability.
In summary, Apache Kafka proves to be versatile and essential across various industries and use cases. It facilitates real-time communication, ensures data integrity, enables efficient event streaming, replaces classical messaging software, and supports high scalability and fault tolerance. With its robust capabilities, Apache Kafka continues to be the go-to solution for organizations seeking to streamline their data processing and communication systems.
Fault tolerance and high scalability: Users have consistently praised Apache Kafka for its fault tolerance and high scalability. Many reviewers have stated that Kafka excels in handling large volumes of data and is considered a workhorse in data streaming.
Ease of administration: Reviewers appreciate Kafka's ease of administration, noting that it offers an abundance of options for managing and maintaining queues. Multiple users have mentioned that the platform allows for easy expansion and configuration of cluster growth, making it straightforward to administer.
Real-time streaming capabilities: Kafka's real-time streaming capabilities are seen as a significant advantage by users. Several reviewers have highlighted the platform's ability to handle real-time data pipelines and its resistance to node failure within the cluster. This feature enables users to process asynchronous data efficiently and ensures continuous availability of the system.
Difficulty Monitoring Kafka Deployments: Some users have found it difficult to monitor their Kafka deployments and have expressed a desire for a separate monitoring dashboard that would provide them with better visibility into their topics and messages.
Steep Learning Curve for Creating Brokers and Topics: The process of creating brokers and topics in Kafka has been described as having a steep learning curve by some users, who believe that it could be simplified to make it more accessible.
Outdated Web User Interface: The web user interface of Kafka has not been updated in years, leading some users to feel that it lacks a streamlined user experience. They express the need for a more modern interface instead of relying on third-party tools.
Users have recommended using Apache Kafka for various messaging platform requirements. It integrates easily with multiple programming languages, offers stream processing capabilities, distributed data storage, and the ability to handle multiple requests simultaneously.
Another common recommendation is to consider Apache Kafka as a messaging broker due to its extensive feature set and guaranteed delivery of data to consumers. Users find it highly supported and widely used within the community.
Users also recommend Apache Kafka for streaming large amounts of data. They praise its scalability and ease of use, although they mention that manual rebalancing of partitions may be required when adding or deleting nodes. Additionally, users appreciate that Kafka allows connections between multiple producers and consumers with low resource consumption.
Overall, Apache Kafka is regarded as a practical choice for message processing systems, data streaming, and handling large volumes of data due to its stability, scalability, and diverse features.
Attribute Ratings
Reviews
(1-9 of 9)Apache Kafka - Default Choice For Large Scale Messaging
- Well known and known set of tools from setup to admin.
- Scalability.
- Fit for use in both onprem, and cloud-base use cases.
Apache Kafka - FTW
- Clustering
- HA
- open source
- Community
A Deep Dive into the Power and Potential of Apache Kafka
- Event-Driven Architecture
- Super fast processing capability & data retention
- Fault Tolerance & High Volume Processing
Kafka for tracking changes
- High throughput
- Low latency
- Fault tolerance
Confluent Kafka for messaging.
- Brokering & message consumption.
- Cluster & topic definition.
Kafka: Best Streaming Platform on the Market
- Performance
- Scalibility
- Realtime
Kafka events; helping your company work with data
- Reporting the number of records in a Topic
- Providing offset information for all consumers in a given Topic
- The ability to make adjustments to Topics on the fly with minimal impact on processes.
Apache Kafka - a must have tool for distributed toolkit
- Partitioning.
- Message retention configuration.
- Integration with schema registry - Avro.
Kafka is an excellent tool for data integration!
- Data retention
- Processing power
- Connectivity