![]() ![]() In the second part, Timeplus directly analyzes raw streaming data in the Redpanda topics without persisting them. There are two parts of this demo, in the first part, Timeplus ingests data from Redpanda, conducts data analysis and then delivers the analysis results to Redpanda. Here is a sample of the raw stream event: In this demo, the topic car_live_data in Redpanda is a JSON stream, which contains the live status of each car including car id, speed, longitude, latitude, etc. For more details, please see the use cases. Timeplus dataloader is the performance test tool we used to make such a performance test.Ĭheck out this short video demonstrating how easily and powerfully Redpanda and Timeplus can be combined to analyze data in real-time. To help us better identify the more performant choice for developers, the Timeplus team ran a test to measure the end-to-end analytics latency and throughput on top of Apache Kafka and Redpanda. ![]() CREATE EXTERNAL STREAM car_demo (src string) SETTINGS type='Redpanda', brokers='redpanda:9099', topic='car_live_data' Achieving low latency streaming analyticsĪpache Kafka is a popular streaming platform and using Apache Kafka as a platform to ingest upstream data or deliver data downstream, seems like an easy decision to make. ![]() Pairing Redpanda with Timeplus is easy! Timeplus can be configured to use Redpanda with a single command. Timeplus can also directly query the topics in Redpanda as the raw streaming data store.Redpanda can act as downstream sink, responsible for another data hub to manage all streaming analytic results.Redpanda can act as upstream source to Timeplus, responsible for central streaming data hub to manage all streaming data. ![]() Thanks to its Apache Kafka® API-compatibility, Redpanda works seamlessly with Timeplus to provide a platform to quickly turn streaming data into real-time actionable insights. Redpanda is a developer-friendly streaming data platform that combines operational simplicity, speed and reliability within unified access to real-time and historical data. Streaming analytics with Redpanda and Timeplus Intuitive: Users get speed, ease-of-use, and advanced analytics functions, both in the cloud or at the edge, and can quickly act on data simultaneously as it arrives. Powerful: Users can quickly analyze real-time streaming data, while simultaneously connecting to historical data assets, all from one SQL query. Timeplus enables users to make real-time analytics:įast: Timeplus can achieve 4 millisecond end-to-end latency, and 10 million + EPS benchmark even in a single commodity machine. This empowers enterprises to extract substantial value from data before it goes obsolete. Timeplus provides a dynamic schema for real-time analytics, bringing flexibility to data querying and processing. Timeplus is a purpose-built streaming analytics platform that solves enterprises’ need for easy-to-implement real-time analytics. Timeplus can provide a fast, powerful and intuitive streaming analytics platform to turn streaming data into real-time actions. Specifically, Redpanda can provide a fast, scalable, reliable, and simple streaming platform to collect and manage streaming data. In this blog, we will demonstrate how Timeplus and Redpanda enable a streaming-first approach to help solve many of developers core issues they face deploying real-time analytics capabilities. But these “real-time superpowers” have been too expensive and complicated to develop for most enterprises.( 1)( 2) Real-time analytics and streaming data infrastructure are transforming the digital business landscape. ![]()
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