Data Architect at a government with 10,001+ employees
Real User
2024-01-26T17:21:00Z
Jan 26, 2024
We use Apache Kafka with Confluent Cloud for specific real-time transaction use cases, both on-premise and in the cloud. We have been using Confluent Cloud for about five years. We initially used it for data reputation, then expanded to microservices integration and Kubernetes, focusing on improving data quality and enabling real-time location tracking. We configure it for data transactions across various topics and partitions, depending on the specific use case and required throughput. From an IT perspective, I've used this product across all domains: system development, operations, data management, and system quality.
Senior Architect at a outsourcing company with 501-1,000 employees
Real User
Top 20
2023-11-29T07:23:00Z
Nov 29, 2023
Our use case is for real-time data integration. It was a preferred tool for this purpose. Additionally, we employed Azure EventHub, another service, as an indicator for real-time data in a couple of larger programs focused on integrating real-time data and visualization.
I use it for real-time processing workloads. So, in some instances, it's like IoT data. We need to put it into a data lake. However, we are using Redpanda, which is still a Kafka protocol. Lots of real-time processing and high-velocity data are the use cases.
We had a legacy website collecting user data as they logged into the portal. We wanted to capture that information in Snowflake and store it in a mobile app. We used Apache Kafka on Confluent Cloud for real-time data streaming.
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We use Apache Kafka with Confluent Cloud for specific real-time transaction use cases, both on-premise and in the cloud. We have been using Confluent Cloud for about five years. We initially used it for data reputation, then expanded to microservices integration and Kubernetes, focusing on improving data quality and enabling real-time location tracking. We configure it for data transactions across various topics and partitions, depending on the specific use case and required throughput. From an IT perspective, I've used this product across all domains: system development, operations, data management, and system quality.
Our use case is for real-time data integration. It was a preferred tool for this purpose. Additionally, we employed Azure EventHub, another service, as an indicator for real-time data in a couple of larger programs focused on integrating real-time data and visualization.
I use it for real-time processing workloads. So, in some instances, it's like IoT data. We need to put it into a data lake. However, we are using Redpanda, which is still a Kafka protocol. Lots of real-time processing and high-velocity data are the use cases.
We had a legacy website collecting user data as they logged into the portal. We wanted to capture that information in Snowflake and store it in a mobile app. We used Apache Kafka on Confluent Cloud for real-time data streaming.