There are numerous possibilities that can be explored. While it may be challenging to fully comprehend the potential advantages, one key aspect is the ability to establish a proper sequence of events rather than simply dealing with a jumbled group of occurrences. These events possess their own timestamps, even if they were not initially provided with one, and are arranged in a chronological order that allows for a clear understanding of the progression of the events.
We appreciate the ability to persistently and quickly write data, as well as the flexibility to customize it for multiple customers. Additionally, we like the ability to retain data within Apache Kafka and use features, such as time travel to access past customer data. The connection with other systems, such as Apache Kafka and IBM DB2.
Kafka allows you to handle huge amounts of data and classify it into different categories. If you have huge amounts of data, Kafka is a very good solution for data classification.
The most valuable feature of Apache Kafka is the clustering which is very easy to scale and we have multiple servers all over our platforms. It has been useful for stability and performance.
Apache Kafka has good integration capabilities and has plenty of adapters in its ecosystem if you want to build something. There are adapters for many platforms, such as Java, Azure, and Microsoft's ecosystem. Other solutions, such as Pulsar have fewer adapters available.
This is a system for email and other small devices. There has been a relay of transactions continuously over the last two years it has been in production.
With Kafka, events and streaming are persistent, and multiple subscribers can consume the data. This is an advantage of Kafka compared to simple queue-based solutions.
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.
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...
Apache Kafka is an open-source solution that can be used for messaging or event processing.
Apache Kafka's most valuable features include clustering and sharding...It is a pretty stable solution.
The publisher-subscriber pattern and low latency are also essential features that greatly piqued my interest.
It is a stable solution...A lot of my experience indicates that Apache Kafka is scalable.
Kafka can process messages in real-time, making it useful for applications that require near-instantaneous processing.
Kafka's most valuable feature is its user-friendliness.
There are numerous possibilities that can be explored. While it may be challenging to fully comprehend the potential advantages, one key aspect is the ability to establish a proper sequence of events rather than simply dealing with a jumbled group of occurrences. These events possess their own timestamps, even if they were not initially provided with one, and are arranged in a chronological order that allows for a clear understanding of the progression of the events.
We appreciate the ability to persistently and quickly write data, as well as the flexibility to customize it for multiple customers. Additionally, we like the ability to retain data within Apache Kafka and use features, such as time travel to access past customer data. The connection with other systems, such as Apache Kafka and IBM DB2.
Kafka is scalable. It can manage a high volume of data from many sources.
Kafka allows you to handle huge amounts of data and classify it into different categories. If you have huge amounts of data, Kafka is a very good solution for data classification.
The open-source version is relatively straightforward to set up and only takes a few minutes.
The most valuable feature of Apache Kafka is Kafka Connect.
The solution is very scalable. We started with a cluster of three and then scaled it to seven.
It seemed pretty stable and didn't have any issues at all.
The most valuable feature of Apache Kafka is the clustering which is very easy to scale and we have multiple servers all over our platforms. It has been useful for stability and performance.
Deployment is speedy.
It is a useful way to maintain messages and to manage offset from our consumers.
Good horizontal scaling and design.
Kafka is an open-source tool that's easy to use in our country, and the command line interface is powerful.
Apache Kafka has good integration capabilities and has plenty of adapters in its ecosystem if you want to build something. There are adapters for many platforms, such as Java, Azure, and Microsoft's ecosystem. Other solutions, such as Pulsar have fewer adapters available.
The stability is very nice. We currently manage 50 million events daily.
This is a system for email and other small devices. There has been a relay of transactions continuously over the last two years it has been in production.
I like Kafka's flexibility, stability, reliability, and robustness.
It is the performance that is really meaningful.
Robust and delivers messages quickly.
With Kafka, events and streaming are persistent, and multiple subscribers can consume the data. This is an advantage of Kafka compared to simple queue-based solutions.
The solution is very easy to set up.
The most valuable features are the stream API, consumer groups, and the way that the scaling takes place.
valuable features relate to microservices architecture and working on KStream and KSQL DB as a microservices event bus.
The most valuable feature is the support for a high volume of data.
Resiliency is great and also the fact that it handles different data formats.
The processing power of Apache Kafka is good when you have requirements for high throughput and a large number of consumers.
When comparing it with other messaging and integration platforms, this is one of the best rated.
The stream processing is a very valuable aspect of the solution for us.
It is easy to configure.
We get amazing throughput. We don't get any delay.
The most important feature for me is the guaranteed delivery of messages from producers to consumers.
The most valuable feature is the performance.
It's an open-source product, which means it doesn't cost us anything to use it.
Scalability is very good.
Kafka provides us with a way to store the data used for analytics. That's the big selling point. There's very good log management.
The most valuable feature is that it can handle high volume.
It's very easy to keep to install and it's pretty stable.
It eases our current data flow and framework.