From the horse's mouth

We are often asked about the advantages of using SQLstream Blaze with Kafka. Here's our answer, as formulated by Damian Black, our CEO, during one of the webinars in our Q1 streaming series.

Levels of engagement

Add streaming to legacy

Many of our customers begin with legacy systems for data collection, sometimes using a store-then-query model, and are upgrading to a stream environment. With Kafka as a connector, they can easily feed legacy and new data streams into Blaze for processing.

data processing

Improve performance

Some clients are already doing stream processing, but need performance improvements. Kafka makes it easy to plugin our capabilities to a streaming architecture and bring the processing speed up to 1million records per second per core.

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If you're assembling a new stream computing system from scratch and are looking for best-of-breed solution from the start, Blaze is the only architecture built from the ground up for complete streaming data processes.

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SQLstream Blaze on Kafka

Since SQLstream Blaze processes data at scale and Kafka processes messages at scale, the two technologies naturally complement each other. The resulting distributed data management architecture enables real-time processing for Fast & Big Data.