The complexity of streaming data technologies – not just streaming video but any kind of streaming data – has created a headache around dealing with that high-speed data processing.
Accordingly, companies like Spark and Flink have sprung up to address this ksqlDB. Many are either either Java-based solutions or SQL-based analytics solutions. However, U.K. startup Quix says it is a platform for developing event-driven applications with Python, which can have uses in, say, physics-based data modelling and anomaly detection in machine learning.
It’s now raised an £11 million / $12.9 million Series A funding round led by London-based VC MMC Ventures, with participation from existing investors Project A Ventures (out of Berlin) and Passion Capital (London).
In a statement, Mike Rosam, co-founder at Quix, said: “Many companies are struggling to combine raw technologies like Kafka into real-time data capabilities… This new capital will fuel our mission to simplify event-driven data engineering so that more companies can build modern data-intensive apps.”
Oliver Richards, partner at MMC Ventures, added: “We have been doing an increased amount of research in the data infrastructure space, it is clear that there is a growing demand for real-time streaming data, both across consumer and B2B use cases.”