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We also note that Redpanda performs even better when handling large batches of data. The test result shows that Redpanda + Timeplus achieves 6ms end-to-end query latency (P90) with 2.4 million EPS, which is 8 times faster than Apache Kafka + Timeplus combination. The following chart shows the output of our tests for query latency. Redpanda vs Apache Kafka® performance comparison Here is the hardware configuration of these test machines: The query statement is a live event query with the filtering condition like this: It means when a user gets an analysis result, this analysis is based on the most recent data. Latency is an important metric to evaluate a real-time system, it shows how fast the newly generated data gets processed by the query engine instead of how fast the query is itself. Timeplus has an internal metric service that stores all t0/t1 during the test and provides the final statistical result. The key test objective is to measure end-to-end query event latency, which is defined as t1-t0 (refer to the deployment diagram), where t0 is the time when the streaming event enters Redpanda or Kafka, and t1 is the time when Timeplus emits the query result. One dedicated machine is used to run the query client. Redpanda/ Apache Kafka and Timeplus are deployed into one dedicated machine to simplify deployment. Timeplus subscribes to the streaming data from Apache Kafka or Redpanda, and runs the queries. Streaming data is sent to Apache Kafka or Redpanda, which simulates the real case where the user needs an event hub to store real-time streaming data. Pairing Redpanda with Timeplus is easy! Timeplus can be configured to use Redpanda with a single command.Įnter fullscreen mode Exit fullscreen mode 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.

Fast: Timeplus can achieve 4 millisecond end-to-end latency, and 10 million + EPS benchmark even in a single commodity machine.

Timeplus enables users to make real-time analytics: 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.