My main use cases for Apache Kafka are for a big project where Apache Kafka is one of the main components for sending messages and receiving them.
External reviews
External reviews are not included in the AWS star rating for the product.
Enhancement of message distribution and security through diverse connection support
What is our primary use case?
What is most valuable?
I appreciate that Apache Kafka is fast and secure thanks to implementing it with AWS, allowing me to secure it on a high level. It's fast with a good connection, and the different types of connections are a good thing for me, helping our team that uses it, which is very helpful.
The impact of Apache Kafka's scalability features on my organization and data processing capabilities depends on how many messages each company wants to receive. With a high throughput, it helps to have more brokers and partitions. If you are a company that doesn't need that many messages, I won't say it will help you a lot, but on the other hand, it can change significantly.
What needs improvement?
I don't actually think about anything they could improve about Apache Kafka, as our use cases using it are more or less on the basic level, so I didn't think about any kind of improvement.
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.
For how long have I used the solution?
I have been using Apache Kafka for about six months.
What do I think about the stability of the solution?
I use Apache Kafka topic partitioning feature for my system stability.
This feature of Apache Kafka has helped enhance our system stability when handling high volume data because we have thousands of messages in a small amount of time, so partitioning helps us distribute all the messages that we receive between all partitions, which helps us to be stable.
What was our ROI?
I have seen some ROI from Apache Kafka, although I can't recall specifics.
Which other solutions did I evaluate?
I am saying that Apache Kafka has better security than other options, even though I don't know about them because we didn't explore them. We simply knew that Apache Kafka is the base where you should use it, so we went with that.
What other advice do I have?
At this point, I don't have any specific examples to share. I don't actually remember if I have used Apache Kafka Connect for integrating various data sources and sinks within my organization. I currently don't have any examples of how it has benefited my organization.
On a scale of one to ten, I would rate Apache Kafka an eight.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
An open-source solution that can be used for messaging or event processing
What is most valuable?
Apache Kafka is an open-source solution that can be used for messaging or event processing.
What needs improvement?
Apache Kafka has performance issues that cause it to lag.
For how long have I used the solution?
We did a couple of POCs on Apache Kafka for more than two years for messaging and event processing.
What do I think about the stability of the solution?
I rate Apache Kafka an eight out of ten for stability.
What do I think about the scalability of the solution?
I rate Apache Kafka a seven out of ten for scalability.
How are customer service and support?
Since it's an open-source solution, there is no technical support, and users often rely on the community edition.
Which solution did I use previously and why did I switch?
I have previously worked with Confluent and Anypoint MQ. Confluent is completely an event-driven architecture. Anypoint MQ is a typical messaging software and cannot be used for an event-driven architecture.
How was the initial setup?
The solution's initial setup is quite straightforward. You just have to upgrade a couple of configuration files.
What's my experience with pricing, setup cost, and licensing?
Apache Kafka is an open-source solution.
What other advice do I have?
A non-enterprise business with a low message load can use an open-source solution like Apache Kafka.
I would recommend the solution to enterprise businesses depending on their use cases. Suppose an enterprise business doesn't have any integration or a middleware platform and wants to do a greenfield implementation. I'll evaluate the use cases and refer Apache Kafka to them if messaging is needed only for exception handling or transferring the messages.
I have recommended Apache Kafka to some customers who wanted asynchronous messaging for logging purposes. Those messages were not business-critical messages as such.
I would recommend Apache Kafka to other users. Apache Kafka is more relevant when we use open-source integrations and when customers want to reduce the TCO. As an architect, I recommend the solution to customers based on their messaging needs. Apache Kafka and Anypoint MQ are the only two messaging products available today. The open-source Apache Kafka is always recommended if the customer really doesn't want to get into any of the license models.
Overall, I rate Apache Kafka an eight out of ten.
Ingénieur Logiciel Senior
Le produit est bon pour trouver le logiciel adapté aux besoins de l'utilisateur.
L'une des meilleures plateformes gérées pour Kafka
2. La plateforme sert de solution unifiée pour les pipelines de données en temps réel, les applications et les microservices. Offre une large gamme de fonctionnalités dans l'édition entreprise pour une gestion des données en temps réel fiable et évolutive.
3. Intégration facile avec diverses solutions logicielles, contribuant à une augmentation significative de l'utilisation. Les exports de registre de schémas, les outils de surveillance Prometheus sont précieux. Intégrations API impressionnantes et support pour l'Infrastructure as Code (IaaC) via Terraform.
4. Le support de Confluent s'est avéré être un gain de temps et améliore la productivité des développeurs.
Points forts : clusters Kafka fiables, registre de schémas pour la fiabilité des messages, interface web conviviale.
2. L'exportateur de schéma n'est pas entièrement pris en charge dans Terraform.
3. Certains documents Confluent sont obsolètes, nécessitant des recherches externes et Stack Overflow pour la résolution des problèmes. La documentation, en particulier sur le déploiement, n'est pas à la hauteur et n'est pas conviviale pour les débutants.
4. La courbe d'apprentissage globale est élevée, nécessitant des connaissances sur Kafka, les connecteurs et la sécurité.
Offers real-time processing workloads and highly scalability
What is our primary use case?
Lots of real-time processing and high-velocity data are the use cases.
What is most valuable?
I'm happy with the scalability and the ability to kind of replay the topics if you wish. So, it can give you that flexibility.
What needs improvement?
For the original Kafka, there is room for improvement in terms of latency spikes and resource consumption. It consumes a lot of memory.
Resource consumption. It consumes a lot of memory.
For how long have I used the solution?
I have been using it since 2019.
What do I think about the stability of the solution?
I would rate the stability a seven out of ten. There are issues due to latency spikes and resource consumption. It varies quite a bit. It's not very stable. It is a powerful tool; it can work, but it can be problematic sometimes. And that's why I switched to Redpanda.
What do I think about the scalability of the solution?
I would rate the scalability a nine out of ten. One of our clients is an online casino; they have over two million end users.
Which solution did I use previously and why did I switch?
I used RabbitMQ. I switched to Kafka because it is just capable of handling a lot more messages.
And that was because the original Kafka had some performance issues, some latency spikes, and things like that.
How was the initial setup?
The initial setup is easy because they provide documents. So, the documentation makes it easy to set up.
The deployment takes a few hours to set up a production environment and configure it in the cluster. It's pretty straightforward and pretty fast.
What about the implementation team?
I figured it out on my own.
What was our ROI?
There is an ROI.
What's my experience with pricing, setup cost, and licensing?
If you use Confluent Cloud, it's expensive because it needs updates available in the platform, like AWS. But you only pay for what you use. So it's quite affordable considering the value it provides.
It is affordable for me.
What other advice do I have?
Overall, I would rate the solution an eight out of ten. I would advise integrating Kafka with Redpanda. It's easier to work with for most people.
Bonne architecture de diffusion de données
2. Matrice de sécurité sur place capable de gérer plus de 50 millions de comptes
3. Sécurité d'entreprise améliorée par l'IA
2. L'intégration des microservices est encore léthargique.
Confluent Cloud est l'approche la plus facile et la plus fiable pour les clusters Kafka.
- Utilisation du registre de schémas pour la fiabilité des messages
- UX fantastique sur l'interface web
- Intégrations incroyables avec les API
- Support pour Terraform pour IaaC
- L'exportateur de schéma n'est pas entièrement pris en charge dans Terraform
Is very scalable and has been beneficial is in the context of financial trading
What is our primary use case?
I have previous professional experience using Kafka to implement a system related to gathering software events in one centralized location.
How has it helped my organization?
One example of how Kafka has been beneficial is in the context of financial trading. When a trade is executed, it generates an event. I used Kafka to create an application that captures these events and stores them in a topic, allowing for efficient processing in real time.
What is most valuable?
Regarding the most valuable feature in Kafka, I would say it's scalability. The publisher-subscriber pattern and low latency are also essential features that greatly piqued my interest.
What needs improvement?
Maintaining and configuring Apache Kafka can be challenging, especially when you want to fine-tune its behavior. It involves configuring traffic partitioning, understanding retention times, and dealing with various variables. Monitoring and optimizing its behavior can also be difficult.
Perhaps a more straightforward approach could be using messaging queues instead of the publish-subscribe pattern. Some solutions may not require the complex features of Apache Kafka, and a messaging queue with Kafka's capabilities might provide a more complete messaging solution for events and messages.
For how long have I used the solution?
I have been using Apache Kafka for the past 10 years.
What do I think about the stability of the solution?
The stability may improve if the configuration and management aspects become less challenging.
What do I think about the scalability of the solution?
It depends on the configuration., but scalability is one of the best features of Kafka. I would rate it nine out of ten.
How are customer service and support?
Support can vary depending on whether you're using the open source version or a paid one. Our version, the paid console version, offers highly available support, and you can find a wealth of information and assistance from various providers online. However, when I used MSA on AWS, I encountered limited support for it.
How would you rate customer service and support?
Neutral
What was our ROI?
Despite the challenges we faced with configuration and management, I believe the return on investment is safeguarded.
What's my experience with pricing, setup cost, and licensing?
The cost can vary depending on the provider and the specific flavor or version you use. I'm not very knowledgeable about the pricing details.
What other advice do I have?
I believe that when working with Kafka Apache, it's essential to have a specialist who thoroughly understands and can optimize all the available variables within the solution to achieve the desired behavior.
I would rate it an eight out of ten.
Architecture Événementielle - Kafka Fournisseur de Choix
En plus de cela, leur support a été utile.
Pour être juste, si nous avions commencé à utiliser Confluent aujourd'hui, nous n'aurions pas rencontré ces problèmes. Il est clair que Confluent a fait des progrès significatifs depuis que nous avons commencé à les utiliser il y a 2 ans.