I was planning to use the tool for real-time analysis in terms of data processing and real-time analytics workflows. The real-time IoT data comes through with a few challenges, and that is for one time, so it is more like a Kafka topic. I want to actually use multiple Kafka topics where one of them can be directly fed into the data pipeline, another one can be fed into the real-time alert system, and the next one can be fed into machine learning.
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Offers a free version but needs to improve the support offered to users
What is our primary use case?
How has it helped my organization?
The most valuable features of the solution revolve around areas like the latency part, where the tool offers very little latency and the sequencing part. The sequencing part actually helps to aggregate things in a way that I don't need to write another function or kind of sequence it, and I write an aggregate function to figure out the maximum value in the last ten samples.
What needs improvement?
One complexity that I faced with the tool stems from the fact that since it is not kind of a stand-alone application, it won't integrate with native cloud, like AWS or Azure. Apache Kafka has another mask on it, so if users can have a direct service, like Grafana, that can actually be used as a stand-alone tool with Grafana cloud, or you can use a mix of AWS and Grafana, so there is not much difference with it. I expect Apache Kafka to have Grafana's same nature.
The product's support and the cloud integration capabilities are areas of concern where improvements are required.
For how long have I used the solution?
I have been using Apache Kafka for a year.
What do I think about the stability of the solution?
Stability-wise, I rate the solution an eight out of ten.
What do I think about the scalability of the solution?
Scalability-wise, I rate the solution an eight out of ten.
Around four people in my company use the product.
How are customer service and support?
I did not interact much with the product technical support team. I did not have dedicated support that responded to all my queries since I was using the product's free version. I rate the support a seven out of ten.
How would you rate customer service and support?
Neutral
Which solution did I use previously and why did I switch?
I have worked with Databricks. I use Databricks and Apache Kafka simultaneously.
How was the initial setup?
The product's deployment phase is neither complex nor straightforward. As the software has evolved a lot, users can actually keep it even simpler by opting for a plug-and-play model.
The solution is deployed on an on-premises model.
The solution can be deployed in two or three days.
What about the implementation team?
I was involved with the tool's installation process.
What was our ROI?
I cannot comment on the tool's ROI since I did not use it for production purposes.
What's my experience with pricing, setup cost, and licensing?
I was using the product's free version.
What other advice do I have?
I did not come across any scenarios involving fault tolerance because when it comes to the issue data consistency issues, like missing or incorrect value of data are actually part of the system where the data is being fed. Nevertheless here, when it comes to the missing values, I never tried the option, especially whenever a value is missing, that can allow one to impute the value with another parameter.
Speaking about if I incorporated any emerging data stream streaming trends in Apache Kafka workflows, for example, utilization of AI, I would say that I use it as a local system, so if I have an EC2 server where I kind of read the sample and then populate the regression and reintegration model on top of it, but that is done locally and not on the cloud.
I recommend the product to those who plan to use it. I like Kafka and Flink, and I want to actually create a system in AWS mainly for real-time streaming so that I don't need to worry about multiple data copies.
Considering the improvements needed in the product's support, and the cloud integration capabilities, while looking at the simplicity during the installation phase, I rate the tool a seven out of ten.
Which deployment model are you using for this solution?
On-premises
A distributed event store and stream-processing platform to build real-time streaming data pipelines and applications
What is our primary use case?
We use Apache Kafka to process messages, specifically payment type messages, and incorporate the data from those messages into our analytics and reporting. It utilizes data from additional sources in real-time for our analytics and reporting purposes.
What is most valuable?
The real-time nature and the ability to use multiple offsets are the most beneficial features of Apache Kafka for our data streaming needs. This allows us to replay the same messages using different offsets. Although I haven't set up Kafka's scalability and fault tolerance myself, I know it can be configured with redundancy and fallback options. We primarily consume the messages using different clients, so the setup for fault tolerance and redundancy is transparent to us.
It's quite flexible and comparable to other solutions like ActiveMQ in terms of features and guarantees, especially with offsets for message handling. While ActiveMQ may be preferred in some use cases requiring guaranteed message delivery, Kafka's offset management provides similar functionality. Overall, I would recommend Kafka for real-time data streaming without hesitation.
What needs improvement?
The main challenge we faced while integrating Apache Kafka with other tools was setting up SSL and securing connections. Managing certificate changes and ensuring all clients connect smoothly, especially outside Kubernetes environments, posed ongoing challenges. Once initially set up, maintaining and sharing these security configurations became more manageable, but ensuring compatibility across different environments remained a continuous effort.
For how long have I used the solution?
I have been using Apache Kafka for the last five years.
What do I think about the stability of the solution?
I would rate the stability nine out of ten.
What do I think about the scalability of the solution?
I would rate the scalability nine out of ten.
How are customer service and support?
The technical support, typical for open-source solutions, is also responsive and helpful.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
We switched to Kafka from paid solutions like IBM's MQ due to cost considerations, finding Kafka's multiple offsets and popularity advantageous.
How was the initial setup?
Installation is straightforward, taking less than an hour on Linux, though more complex setups like failover can require more effort.
What was our ROI?
Apache Kafka isn't a major part of our processing yet. Much of our processing is batch processing with data from APIs and other sources. So, it hasn't contributed significantly to return on investment. However, in other areas where we use Kafka extensively for data processing before persisting the data, it has provided quite a bit of return on investment.
What's my experience with pricing, setup cost, and licensing?
As for pricing, Kafka is open-source, so it's free to install and use.
What other advice do I have?
I rate Apache Kafka a nine out of ten for its performance, features, and community support.
Which deployment model are you using for this solution?
Hybrid Cloud
The product is scalable and provides good connectors, but the ability to connect the producers and consumers must be improved
What is our primary use case?
We use the solution for analytics for streaming. We also use it for fraud detection.
What is most valuable?
The Kafka Streams library gives quite a bit of functionality. The connectors provided by the solution are valuable.
What needs improvement?
The ability to connect the producers and consumers must be improved. It's still a pain point because a lot of development goes into it.
For how long have I used the solution?
I have been using the solution for seven to eight years.
What do I think about the stability of the solution?
For what it does, the tool is very stable. It is a message broker. It receives the messages and holds them for producers and consumers. It's usually everything around Kafka that has stability problems because Kafka does exactly what it's supposed to do.
What do I think about the scalability of the solution?
Scalability is one of the main selling points of the tool. The additional nodes we add give us the additional storage capacity we need. I rate the scalability a ten out of ten. The solution is used across multiple domains in our organization. I use the product daily. It’s a continuously growing platform.
How are customer service and support?
Apache doesn't provide support. There are sites we can go to for information, but there's no support team for Apache. There are companies like Confluent and HPE that provide support for the solution.
Which solution did I use previously and why did I switch?
We also use Flink and other streaming tools. We use Apache Kafka in addition to other technologies because of the requirement and the business use cases.
How was the initial setup?
It is super easy to set up. I rate the ease of setup a ten out of ten. However, building and administration get quite difficult. It takes three months to make things production-ready.
What about the implementation team?
The deployment was done in-house. We used the tools that we have in our CI/CD pipeline. We needed three people for the deployment. The infrastructure team maintains the tool. The infrastructure team has three to ten members.
What was our ROI?
We see an ROI on the product. If we don't have a tool to buffer the amount of traffic coming in from high-traffic sites, we cannot use the data. Apache Kafka gives us a resting area where we can push as much information as we want to. It’s picked up by consumers when they need it.
It’s a huge return on investment. Otherwise, we must have a system tied to the producer waiting for the consumer to consume before we can do anything with the rest of the messages. A solution like Kafka provides us with a buffer to consume the data as we choose to.
What's my experience with pricing, setup cost, and licensing?
The price depends on who we are getting the product from. If we buy it from Confluent, we always have to try to negotiate the price. The price is always negotiable.
What other advice do I have?
Overall, I rate the product a six out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
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
Qu'aimez-vous le plus à propos de the product?
Haute disponibilité et débit. C'est très fiable.
Que n’aimez-vous pas à propos de the product?
C'est coûteux et souvent nous devons penser à des alternatives.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Kafka est notre composant principal pour la livraison d'événements à divers services.
"Un changement de paradigme pour la gestion des données en temps réel"
Qu'aimez-vous le plus à propos de the product?
Avec les sujets Kafka, il est possible de configurer facilement un modèle pub/sub et de fournir aux producteurs et aux consommateurs une visibilité complète de bout en bout à l'aide de Confluent Center. Simple à mettre à l'échelle grâce à l'ajout de courtiers et aux déploiements de mises à jour/patchs logiciels "sans temps d'arrêt".
Que n’aimez-vous pas à propos de the product?
Confluent n'a rien que je n'aime pas. Au lieu de cela, ils se concentrent sur l'amélioration du flux de données à partir du CDC.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Notre architecture est en train d'être redéfinie en utilisant des microservices pilotés par des événements et des pipelines de traitement de flux, avec Kafka servant de seule source de vérité. Étant donné que les développeurs de notre équipe doivent encore passer par une courbe d'apprentissage spécifique et un changement de paradigme, la productivité est encore insuffisante.
Flexibilité d'utilisation
Qu'aimez-vous le plus à propos de the product?
Confluent a rendu notre traitement d'événements extrêmement fluide. Des millions d'événements ont été déclenchés et tous ont été traités sans effort. L'installation, la configuration et les intégrations avec la base de données relationnelle étaient la cerise sur le gâteau. En tant qu'administrateur et développeur, la documentation était si facile et pertinente que nous avons effectivement passé moins de temps que prévu.
Que n’aimez-vous pas à propos de the product?
Manque de ressources d'apprentissage tierces et de soutien communautaire
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Attributions des utilisateurs dans le marketing de performance.
Le produit est bon pour trouver le logiciel adapté aux besoins de l'utilisateur.
Qu'aimez-vous le plus à propos de the product?
Le produit est bon et diffuse toutes les données sans aucun problème.
Que n’aimez-vous pas à propos de the product?
Il faut faire quelque chose concernant l'intégration qui sera facile.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
J'ai essayé de diffuser des messages et des notifications depuis mon application. Cela a fonctionné facilement et sans problème.
Têtes sur avec Kafka natif
Qu'aimez-vous le plus à propos de the product?
Nous n'avons pas besoin de nous inquiéter pour le gardien de zoo.
Que n’aimez-vous pas à propos de the product?
Le fichier Docker compose n'est pas très faisable, le courtier ne démarre pas d'un seul coup et doit être redémarré encore et encore. C'est la principale raison pour laquelle nous sommes passés à Kafka natif.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Facile à configurer sur mon serveur, changer la configuration n'est pas non plus difficile comme en natif.
Le meilleur de la plateforme de diffusion de données
Qu'aimez-vous le plus à propos de the product?
Quelques bonnes choses que j'aime à propos de Confluent
Plateforme unifiée
Intégration Apache Kafka
Évolutivité et performance
Capacités de streaming
Plateforme unifiée
Intégration Apache Kafka
Évolutivité et performance
Capacités de streaming
Que n’aimez-vous pas à propos de the product?
La configuration de Confluent peut être un peu difficile si vous avez peu de connaissances en Kafka.
Quels sont les problèmes que the product résout, et en quoi cela vous est-il bénéfique?
Application pilotée par des événements avec un support de niveau entreprise.
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