Redpanda serves two primary purposes for our organization. First, we use it as a drop-in replacement for Kafka. Second, we utilize it for streaming analytics. We do not use Redpanda for IoT data streaming, though it has been quoted as suitable for that use case. IoT data streaming is actually a superset of our use cases. Recently, we have started using it for AI analytics as well.
Our main use case for Redpanda is to send a large volume of messages and consume those messages, essentially processing them. Redpanda is renowned for handling very high throughput. Redpanda, or Kafka, is able to process billions of messages.
Big Data Teaching Assistant at Center for Cloud Computing and Big Data, PES University
Real User
Top 5
Oct 25, 2024
I have worked with Redpanda for the past two to three months. Mainly in the tech industry or software industry, there's a huge rise of streaming data. Redpanda serves as a very reliable and fast message broker, which lets you build applications asynchronously. The major use case is for my project specifically, we're using it for a monitoring system that we're building.
Lead DevOps Engineer at Activelobby Information Systems Pvt Ltd.
Real User
Top 5
Sep 19, 2024
We handle high volumes of telemetry data and operate under stringent latency requirements, with our data pipeline demanding sub-second response times. Redpanda seamlessly integrates into our data plane, particularly as a message broker system, where performance is absolutely critical. Its low-latency capabilities and robust performance have been essential to meeting our operational demands
We use the tool for a simple use case. We use it for data streaming and data normalization. We receive a lot of messages from many different systems. We normalize them and highlight errors. We get 5000 to 6000 messages per minute, so we dump them in the database to handle the load. We use the tool for microservices.
Redpanda offers a modern, intuitive interface with efficient resource usage, seamlessly integrating with Kafka, and enhancing performance through fast operations and reliable support. Organizations benefit from its memory efficiency and high performance for demanding data workloads.Built on a C++ foundation, Redpanda integrates easily with Kafka clients and stands out for fast operations, simplified Docker setup, and effective metrics monitoring. Performance is enhanced by memory efficiency...
Redpanda serves two primary purposes for our organization. First, we use it as a drop-in replacement for Kafka. Second, we utilize it for streaming analytics. We do not use Redpanda for IoT data streaming, though it has been quoted as suitable for that use case. IoT data streaming is actually a superset of our use cases. Recently, we have started using it for AI analytics as well.
Our main use case for Redpanda is to send a large volume of messages and consume those messages, essentially processing them. Redpanda is renowned for handling very high throughput. Redpanda, or Kafka, is able to process billions of messages.
I have worked with Redpanda for the past two to three months. Mainly in the tech industry or software industry, there's a huge rise of streaming data. Redpanda serves as a very reliable and fast message broker, which lets you build applications asynchronously. The major use case is for my project specifically, we're using it for a monitoring system that we're building.
We handle high volumes of telemetry data and operate under stringent latency requirements, with our data pipeline demanding sub-second response times. Redpanda seamlessly integrates into our data plane, particularly as a message broker system, where performance is absolutely critical. Its low-latency capabilities and robust performance have been essential to meeting our operational demands
We use the tool for a simple use case. We use it for data streaming and data normalization. We receive a lot of messages from many different systems. We normalize them and highlight errors. We get 5000 to 6000 messages per minute, so we dump them in the database to handle the load. We use the tool for microservices.