Confluent Reviews

We collect service log data with Confluent and use it for fraud detection in game services.

We are a game service company, and Confluent has helped us improve our quality of service.

The Schema Registry service could be improved.

I would like a bigger knowledge base of other use cases and more technical forums. It would be good to have more flexible monitoring features added to the next release as well.

I've been using Confluent for about two years.

For stability, I would give this solution a rating of seven out of ten.

I would rate the scalability of the solution at eight out of ten. We have 20 people who use Confluent in our organization now, and we hope to increase usage in the future.

I would rate the solution's technical support at seven out of ten.

Neutral

On a scale from to ten, where one is difficult to set up and ten is easy to set up, I would rate this solution's initial setup at six. It was quite difficult.

The deployment took about a week. We had a team of four people for the deployment. A team of two handle the maintenance.

On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs.

We evaluated Kinesis and MSK, but chose Confluent because we wanted to use its RBAC feature. Also, the other solutions did not have a feature to clear storage.

I would recommend Confluent as an alternative to those who are unfamiliar with Kafka. Overall, I would rate Confluent at eight out of ten.

I use the tool to create documentation that needs particular specifications.

The documentation process is fast with the tool.

The product should integrate tools for incorporating diagrams like Lucidchart. It also needs to improve its formatting features. We also faced issues while granting permissions.

I have been working with the tool for three years.

The tool is stable.

The solution is scalable. My company has more than 25,000 users of the tool.

The tool’s initial setup is complicated.

I would rate the overall solution a nine out of ten. Confluent is a great tool for business analysts and project managers.

Our use cases include data streaming, enterprise architecture, integrations, and complete data saving needs, some AI workloads, and standardization. We work on all of these.

The biggest benefit is that it is open source. You have the flexibility of opting or not opting for enterprise support, even though the tool itself is open source. 

The second benefit is it's very modern and built on Java and Scala. You can extend the features very well, and it doesn't take a lot of effort to do so.

Then the performance and community support, which we get while we do any POT, proof of theory work. The community support we receive is also really good.

The knowledge base on the Confluent website is also a good benefit. 

In terms of the valuable features, first would be scalability, then open source. You can use it for POCs, and if you are going to production with this technology, then you can opt for platinum support. The design of the product is extremely well built and it is highly configurable.

Whether you have a custom use case or out-of-the-box implementation, you can configure it according to your needs. The tool is very flexible, so you can configure it according to your use case and it's easy to administer. Because it's open-source, you're transparent as well. Nothing is a black box when you are working with Confluent.

You can extract and look at the code of what's happening. You can customize the code also because it's open source. I find all these features very interesting and appealing.

It would be great if the knowledge based documents in the support portal could be available for public use as well. If Confluent would publish the knowledge base, best practices, proper documentation; that would be helpful for folks who do not have support lines or are just assessing whether they can fit Confluent into their use case.

I have been working with Confluent for more than four years.

Confluent is a reliable product.

I have been working on Confluent with two companies and around ten people. We use it on a daily basis. It's basically a vertical and it integrates all the sources.

We use the solution on-premise with enterprise support. This is an open-source technology and the setup I was working on was on-premise. There are various features of the platinum enterprise support with Confluent.

We can go to them for knowledge modules and best practices. We can reach out to Confluent regarding any product which is currently active or if we identify a bug in any product. We reach out with a support request. I'm satisfied with the support.

While I was using Confluent, I worked on use cases involving other traditional message use and conventional streaming platforms. The Confluent platform actually outlines everything, so it's a great product in this field.

The implementation is somewhere in between simple to moderate. It depends on the use cases, but it is not a very difficult tool to handle. If you have a team of IT professionals then it takes less time to scale to Confluent. The setup is rather simple and the architecture is microservices-based.

A team of three to five people would easily implement. Again, I'm talking about designing and a POC implementation. So whenever you move to production or scalability, you just have to replicate the configurations.

For a general mini architecture, you can deploy very easily with three to five people.

The timeframe to implement depends on the complexity of the use cases. Sometimes it takes a month or two; sometimes it can take a week or two. 

You have to pay additional for one or two features. The monitoring simple solution call conference control center and Confluent replica for disaster recovery. You have to pay for these two use components, but it is included in the support package.

The solution requires a support team. A minimum of two people are required to administer and handle the support activities in the event of outage. So any service will need, so Confluent is not no different in that perspective.

The support is very good and it's open source. Companies can easily pre-assess whether it fits their needs. They can even do performance benchmarking. 

I would give the solution a nine out of ten.

Our company has a wide portfolio of use cases in which we recently changed the entire landscape. We use Confluent to share useable dat across all portfolios through a central place.

We use dedicated clusters with four CKs. On standard clusters we are using just the standard configurations that comes out of the box in Confluent Cloud.

With Confluent Cloud we no longer need to handle the infrastructure and the plumbing, which is a concern for Confluent. The other advantage is that all portfolios have access to the data that is being shared.

We are still in the discovery phase. Currently, it's the introduction and acceptance phase for all the portfolios and helping them adopt the platform. Portfolios are using different features, some are using Publish-Subscribe to log events, some like the features that are similar to Kafka, while others are using ksqlDB or trying the adoption of Schema Registries. 

So far we value the professional service support and the full management side of things like support with infrastructure issues.

Currently, in the early stages, I see a gap on the security side. If you are using the SaaS version, we would like to get a fuller, more secure solution that can be adopted right out of the box. Confluence could do a better job sharing best practices or a reusable pattern that others have used, especially for companies that can not afford to hire professional services from Confluent.

Another area of improvement is on the metric side. The metrics are integrated within the documentation of the metrics and implementation of that metric. This ties back to the requirement of best practices. How to use metrics in the best possible way out of the box.

If you are using Confluent on-prem or cloud-based where you are packaging it within your own cloud infrastructure, there is a lot of documentation for that making it easier. However, if you are using only the SaaS platform, there is less support from Confluent Cloud.

We are still understanding the additional features but we have seen a gap in the features of the fully managed connector. They are lesser fully managed connectors that are relevant to our business requirements so we have requested those fully managed connectors be developed and released within the Confluent Hub portfolio of connectors.

Confluence requires documentation regarding how to manage connectors that are not fully managed, including what parameters are required for each processing connector. The documentation that is provided is not easy to understand.

I have been using Confluent for six months.

The portfolios that we have onboarded onto Confluent Cloud have been performing well. They are stable without any issues.

Confluent is fairly easy to scale. 

We are using a fully managed solution. Confluent Cloud has an uptime SLA of 99.95 broad for dedicated services, dedicated clusters, and standard clusters that we are using on the cloud. It's the support that we use for the fully managed Confluent Cloud so no maintenance is required. Customer service and support have been perfect.

We recently changed our entire landscape. In the past, every team had its own Kafka instance. Data was siloed and being used by each portfolio differently and not shared across portfolios. We wanted to find a way to share reusable data and make data sharing by default so that it was used across all portfolios and could be leveraged through a central place. We wanted to move away from a self-managed Kafka system and make it fully managed. That's why we started looking at Confluent Cloud.

We are not using the Confluent Platform. How we deploy is by onboarding people to connect to the Confluent Cloud, it's just a networking connection into the Confluent Cloud cluster, not a deployment pipeline.

From a costing perspective, there are costing implications. If you go the cloud route, as you scale there will be cost implications on a per hour basis. Confluent Cloud is more expensive, be mindful of that.

The main point to understand is that Confluent Platform and Confluent Cloud are two different offerings. Confluent Platform requires you to self-manage or manage the Confluent Platform within your cloud environment, rather than Confluent Cloud which uses your applications that are deployed in your cloud to connect to Confluent Cloud.

When you decided to get into Confluent, have clarity on which route you want to go at the outset. Secondly, if you choose Confluent Cloud which is the SaaS platform, have your implementation plan mapped out before you go ahead. Lastly, have your naming conventions, implementation, and securing your topics, your service account or ACLs are all mapped out well.

Support is a 10 out of 10, but overall I would rate Confluent a 7 out of 10.

We primarily use Confluent for service desk and task management. It is also good for knowledge base management.

The solution could have an extra plugin or upgrading feature. In addition, it could have more integration with different platforms and be more compatible.

We have been using this solution for six years, and it is on-site.

It is scalable, and we haven't had any problems so far. We have about 50 users using Confluent in our company. We do not plan to increase usage at this time.

We've had issues in the past and used technical support to resolve them.

We have used Redmine.

I rate this solution an eight out of ten, and I would recommend it to others. We are an open-source organization.

I work in the insurance domain. We stream data in and out Confluent. If financial data is being used most organizations prefer to stay on-premise with their data, but there is a cloud version available. These are the features that Confluent provides.

Confluent has benefited our company because it provides granular access, enterprise support, self-balancing cluster. If there is any data skewness or one server is busy doing some processing, it shifts to the other processor and balances the data between them. There are auto data balances, self-balancing clusters, replication, and role-based access controls.

The most valuable feature that we are using is the data replication between the data centers allowing us to configure a disaster recovery or software. However, is it's not mandatory to use and because most of the features that we use are from Apache Kafka, such as end-to-end encryption. Internally, we can develop our own kind of product or service from Apache Kafka.

They should remove Zookeeper because of security issues.

I have used Confluent within the last 12 months.

The latest version of 6.2.0, has almost everything and it's stable.

The solution is scalable. If you have good hardware, especially for Kafka then it will perform very well. It's easy to scale up, but there are issues scaling down, which may result in losing data.

I don't know exactly how business is doing. We currently are supporting, and we are running up to the threshold of the solution. I'm not sure about the future if we will increase usage.

We have approximately 250 applications running.

We have contacted technical support. We create support tickets, in case of emergencies or when any support is required.

I've been working with the support team for four years. They are good. The level one team will go around the issue by gathering information, but the next level, and the third level development team, are very good.

The installation is straightforward and we use our own ansible-playbook, which was designed similar to CP ansible which is supported by Confluent.

We have two people that do the implementation. We manage four clusters which include integration tests, reproduction, and production. We did the installation with some simple scripts and designing the script takes a couple of weeks.

Confluent requires maintenance because we might see issues with the applications and need to support them. We need to keep checking the performance and we should keep on monitoring them because high critical data will be passing through. There is a need for regular OS patching and any upgrades that Confluent provides. 

Not everybody will be aware of Kafka's technology which means we educate the developers. For example, the properties to be used and what makes optimum performance from the solution.

I have had a return on investment by using Confluent. It's faster than any other technology in real-time. You don't have to wait for your transactions to happen overnight.

The license Confluent is server-based. It depends on the number of services that you are running in the cluster. 

Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance. 

Large organizations, prefer to use open-sourced solutions because they provide a cost reduction. Apache Kafka is open source and there are many other open-source security tools, which can be used that provide features that Confluent offers.

I have evaluated Apache Kafka.

Confluent has improved a lot and they're currently working on version 7.0 where they're removing Zookeeper, which is highly vulnerable to security attacks.

My advice to others wanting to use this solution is for them to use automation wherever it is required and it is a very stable product, not many issues arise If you know how to manage them. Overall, it's a great company and they have excellent software.

I rate Confluent a nine out of ten.

We are providing the solution for real-time data for the banking sector.

We mostly use the solution's message queues and event-driven architecture. Since Confluent has integrated with Kafka, we can utilize its fault tolerance and matrices.

Confluent is expensive, and we face certain limitations while using the tool. Confluent has a good monitoring tool, but it's not customizable. We can only use the existing dashboards. On the other hand, we can utilize maximum customization while using Grafana with Prometheus. Confluent also supports JMX metrics, but using Grafana with Prometheus is very effective.

I have been using Confluent for two months.

I rate the solution’s stability a nine out of ten.

Confluent is a very scalable solution. Since we provide solutions for the banking sector, we need a high throughput of massive data per day.

I rate the solution a seven out of ten for scalability.

Confluent provides really good technical support for its partners.

Positive

I have previously worked with other solutions like MuleSoft Anypoint, Dell Boomi, and Redpanda.

We are currently doing some POCs, which take two to three days based on availability. Sometimes, if the technical people are unavailable, I have to wait for their response and get into meetings.

Confluent is an expensive solution.

On a scale from one to ten, where one is cheap and ten is expensive, I rate the solution's pricing an eight out of ten.

Confluent can be easily integrated with other systems. Most clients don't know the actual use cases of Confluent or Kafka. We explain the real use cases to the clients, like fault tolerance, high throughput, low latencies, and monitoring tools.

I joined my company just one month ago. Working with Confluent for the first time was a bit hard for me because it has a lot of documentation for everything. I need some technical experts to utilize the solution's functionalities. Maintaining the solution is easy because we are part of Confluent, and they are available.

Overall, I rate the solution an eight out of ten.

I use Confluent for real-time data processing and ETL tasks.

I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools.

Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs, as well as enhancing the offset management tool for easier management of offset topics, reprocessing, and message filtering based on predicates.

I would rate the stability of Confluent as a seven out of ten. There is room for improvement in the usefulness of logs and metrics.

I would rate the scalability of Confluent as an eight out of ten. Scalability issues primarily revolve around the challenge of setting up multi-cloud environments, suggesting a need for better replication capabilities between cloud and self-hosted test environments to ease deployment.

We previously used MSK and RabbitMQ. We switched to Confluent because it offers a comprehensive messaging infrastructure solution, including queue functionality, which aligns better with our needs.

I would rate the easiness of the initial setup as a seven out of ten. During the initial setup process, we encountered difficulties with configuring brokers within the same cluster using Terraform, especially for connector configuration, and faced challenges in ensuring proper setup to avoid rebalancing issues.

Our deployment process involved using Jenkins for deploying services, Terraform for resource provisioning, Kubernetes for deploying services and workers, and a dedicated DevOps team managed the deployment, although it is challenging to pinpoint the exact number of people involved specifically for Confluent deployment.

We have seen a 100% return on investment from using Confluent.

I would rate the pricing of Confluent as average, around a five out of ten. Additional costs could include features like multi-tenancy support and native encryption with custom algorithms, which would be beneficial but not currently included in the fixed price.

We use Confluent for real-time data analytics by capturing user activity to build dashboards and implement rate-limiting and pricing strategies for our services.

Confluent improved our data integration process by optimizing bandwidth utilization and reducing latency by threefold through its schema registration error format, enhancing schema security, and ensuring positive impacts on our data processing capabilities.

Confluent's reliability and uptime have been good for us, as it complements our existing fault tolerance mechanisms and offers multi-version support, enhancing our overall data processing capabilities.

The CDC capability with the IBM connector was the most valuable feature for our data streaming needs, serving as a game changer in our data processing workflows.

I highly recommend considering Confluent for its comprehensive set of solutions, particularly when compared to other tools like Spark or Flink. Understanding Kafka's basic constructs and message processing is essential before installation to ensure effective utilization and a clean design for implementation.

Overall, I would rate Confluent as an eight out of ten.