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Apache Kafka

Apache Kafka

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…

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Product Details

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 applications.

Apache Kafka Technical Details

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Comparisons

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Reviews From Top Reviewers

(1-5 of 18)

Apache Kafka - Default Choice For Large Scale Messaging

Rating: 8 out of 10
August 23, 2023
VT
Vetted Review
Verified User
Apache Kafka
5 years of experience
Apache Kafka is really the bedrock of all things streaming and data processing. I cannot imagine if there is any other product that does it better. My last 2 companies used it, and my current one does so as well. If you want your data stream to be organized and sent, Apache Kafka has become the tool of choice. I have dabbled in Azure EventHubs as well, if you are into opensource data streaming, Apache Kafka will take you where you need to be for data lakes and the amount of data that is streamed for the cybersecurity industry that my company is in. Without Apache Kafka, there is no way that my company products can handle the volume of data that we process for our customers.
  • Data streaming is really second to none.
  • Scaling, done right, Apache Kafka is a workhorse.
  • Ease of administration - Although you cannot really compare to Azure EventHubs, but that is comparing between Apples and Oranges.
Cons
  • The web UI has not really changed in years. UX has been refreshed, but a more streamlined UX instead of many 3rd party webUX tools, will be most welcome.
  • Webhooks can still be tricky to troubleshoot at times.
  • CLI monitoring is a learning curve to get it right.
Apache Kafka is well-suited for most data-streaming use cases. Amazon Kinesis and Azure EventHubs, unless you have a specific use case where using those cloud PaAS for your data lakes, once set up well, Apache Kafka will take care of everything else in the background. Azure EventHubs, is good for cross-cloud use cases, and Amazon Kinesis - I have no real-world experience. But I believe it is the same.

A Deep Dive into the Power and Potential of Apache Kafka

Rating: 10 out of 10
August 20, 2023
AP
Vetted Review
Verified User
Apache Kafka
5 years of experience
We use Apache Kafka as an event bus for all our async activities & Micro Service Communication, like sending emails, SMS, and notifications between services and consumers and for event & data processing.
  • Event driven architectures
  • Any use case which requires async data processing
  • Any use case with production and consuming the same data to build business-specific processing
Cons
  • Zookeeper services configuration can be simplified
  • Data logging needs to be secured
  • Restarting & overall management needs to be improved
- It's Super fast - Has some learning curve but once mastered it brings scale - All logics that need producer & consumer kind of implementation (Bulk Notification, etc) - Event-driven architectures can be implemented with Apache Kafka

Apache Kafka - FTW

Rating: 9 out of 10
August 21, 2023
Vetted Review
Verified User
Apache Kafka
6 years of experience
We use Apache Kafka as message broker between our two client facing applications. We used ActiveMQ before but it had shortfalls of high availability and clustering. Kafka solved it on both fronts and gives a good business continuity.
  • High availability
  • performance
  • Admin user interface
Cons
  • zookeeper logs could be better
  • monitoring
It is well suited if you want to use a message broker between two applications with high availability. Its also can be used as streaming replication for data.

Kafka for tracking changes

Rating: 8 out of 10
May 30, 2023
AK
Vetted Review
Verified User
Apache Kafka
3 years of experience
Verified on LinkedIn
We use Apache Kafka to stream order information across systems. An order may go through certain updates through its lifecycle. These updates need to be communicated to the systems in near real time and we rely on Kafka for this.Our business use case is to take these orders up with the insurance companies for approval and thus the order information need to be up to date. Kafka has been excellent at doing this so far.
  • Receiving messages from publisher and sending to consumer in FIFO manner
  • Handling of errors using Dead Letter Queue when message could not be consumed on the consumer end
  • Fault tolerance
Cons
  • Sometimes it becomes difficult to monitor our Kafka deployments. We've been able to overcome it largely using AWS MSK, a managed service for Apache Kafka, but a separate monitoring dashboard would have been great.
  • Simplify the process for local deployment of Kafka and provide a user interface to get visibility into the different topics and the messages being processed.
  • Learning curve around creation of broker and topics could be simplified
Kafka is well suited in scenarios where a message need to be sent to another system in fault tolerant manner. It is useful when the message size could be large and large number of messages could be floating around.
It would be less appropriate or rather an overkill to use Kafka in scenarios where we are sending short messages to offload certain tasks(like invoice generation and sending email) to a worker(like celery). For such use cases, simple queueing solutions like Amazon SQS should suffice.

Confluent Kafka for messaging.

Rating: 6 out of 10
May 22, 2023
Vetted Review
Verified User
Apache Kafka
2 years of experience
Currently consulting and implementing for a bank, we use a cloud-native Kafka solution (Confluent Kafka) for brokering. The solution is well documented, and liked by the developers but lacks certain technical aspects to improve usability and administration.
  • Brokering
  • Topic definition.
Cons
  • Private access to a cluster.
  • Visualisation solutions.
For brokering messages, Confluent Kafka is well suited since it offers a managed solution ready to use. Scenarios where the solution is not very well suited are for example, where pricing is an issue. The solution costs quite a lot for basic usage (for example: for 3 clusters, pricing is above 100k$ a year).
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