Confluent welcomed a group of its key partners to Current 2023 in San Jose this September.
With names including AWS, RedHat, IBM, Google Cloud and Microsoft, other sponsors spanned from Redpanda to Cloudera to Elastic, MongoDB and the company that seems to be at every technology conference on the planet, DataDog.
Among the more vocal partners talking about its technology was the nuttily nattily named Hazelcast, Inc.
Throughout the Kafka-focused community event, Hazelcast hosted sessions to demonstrate its unified real-time data platform, which combines a real-time stream processing engine and fast data store, enhancing Kafka-based solutions and enabling action.
“Stream processing is the next innovative use of streaming data for companies seeking to improve their competitive advantage because it enables them to identify opportunities and threats and act on them in real-time,” said Jakki Geiger, CMO of Hazelcast. “Current 2023 is an excellent opportunity for architects and developers to learn about the transformational potential of a unified real-time data platform and how Hazelcast can level up their Kafka deployments by responding faster to grow revenue, mitigate risk, and improve customer satisfaction.”
At the Hazelcast booth itself we saw developers, architects, data engineers and DevOps professionals learn how to act on streaming data as it flows through the Kafka cluster – using a stream, act, store approach rather than building traditional data pipelines to store data first and act on it later.
Enriched streaming data
Users also looked at chances to enrich streaming data with relevant stored data to provide the context needed to take instant and action – and simplify the development, deployment and maintenance of real-time stream processing architectures; while also taking advantage of high throughput and low latency to deploy fast, scalable applications for running large-scale calculations, simulations and other data- and compute-intensive workloads.
Hazelcast offers a unified real-time data platform designed to take instant action on streaming data.
With a stream processing engine and fast data store integrated into a single solution, businesses can simplify real-time architectures for next-gen applications and AI/ML deployments to drive new revenue, mitigate risk, and operate efficiently – at a low TCO.
“The industry will begin understanding the difference between streaming data and stream processing—and demand the latter,” said Kelly Herrell, chief executive officer, Hazelcast. “Right now, the two get conflated, yet they are radically different and wildly complementary. Streaming data is moving data. It is valuable information about something that is happening right now. Processing data while it’s in flight is the next logical step. That’s stream processing. To stream data and not take advantage of its hidden value – by processing it at the same time – is a huge missed opportunity. Most of our competitors ignore this fact, and as a result, most businesses don’t realise the full potential of their growing reams of streaming data. That means they’re missing out on being able to compete in the real-time economy, which is the one we are in today.
Herrell concludes by stating that the logical next step is using stream processing to power ML-driven applications for inference based on what’s happening in the moment. That will enable companies to meet customer needs instantly, even before the customer is aware that they will be having that need shortly- based on previous patterns.