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Confluent’s successful IPO this week is shining the spotlight on event-driven data architectures and high-performance data streaming platforms based on Apache Kafka. Mountain View-based Confluent was cofounded in 2016 by a trio of programmers — Jay Kreps, Neha Narkhede, and Jun Rao — who developed the event stream processing (ESP) software that became Kafka while working together at LinkedIn.

Having raised around $830 million in its IPO, Confluent saw its stock price open at $44 and close $45.02 on Thursday, an encouraging 25% above its IPO pricing.

As Confluent and Apache Kafka’s stars shine more brightly, other companies building on the open source, high-throughput, low-latency streaming software platform are doubling down on their efforts to bring better streaming apps and tools to market. One such startup is Vectorized, a young company with just a few dozen employees that has built a Kafka API-compatible streaming platform called Redpanda for mission-critical workloads.

VentureBeat sat down with Vectorized founder and CEO Alexander Gallego this week to discuss the future of streaming data application development and the real-time contextualization of data as actionable events, such as the metadata surrounding a retail purchase at a certain time at a specific store location.

Gallego believes the market is hungry to get more out of data streaming capabilities — a lot more. Enterprises want faster access to the rich business intelligence that can be generated from massive amounts of data being captured and put into motion by an ever-increasing host of sensors and endpoints populating our world. But for that to happen, Gallego said, the tools used to create ESP apps need to be greatly simplified.

Simpler tools to harness data in motion

“Streaming has finally hit escape velocity. Banks now give us real-time fraud detection. We are emerging from the experimental and testing phases for autonomous vehicles, which rely on instantaneously streamed data contextualization to operate effectively,” Gallego said.

“Now we need to give simpler tools to developers who want to create new ways to use streaming but are drowning in complexity. We can’t make great apps if we have to search through massive portfolios of products that don’t work well together and are too unwieldy to use efficiently.”

The first production version of Redpanda, released in January, is Vectorized’s attempt at creating that simplified, open source streaming toolkit. While it’s ambitiously intended to eventually replace Kafka, which Gallego claimed is already proving too cumbersome for cutting-edge streaming app development, Redpanda is currently fully compatible with Kafka and is geared toward developing apps more efficiently and more easily in Kafka environments.

For instance, Redpanda dispenses with the need for Zookeeper, a configuration management tool for Kafka apps that Gallego said is difficult and complicated to use. Redpanda also adds native support for the Prometheus event monitoring and alerting application.

Have data, will travel

Industry watchers are bullish on the growth of the event stream processing market. Zion Market Research has projected the global ESP market will grow to $2.6 billion by 2025 at a five-year CAGR of 21.2%.

Gartner began producing dedicated ESP market guides a few years ago. In its most recent Market Guide for Event Stream Processing, the research firm stated that growing demand for real-time business intelligence is pushing the field of data analytics “from transactional to continuous.”

The impact of this is being felt across multiple industries. Confluent and Vectorized are strongest in areas like retail, finance, social media, and CRM. Companies like Adapdix are focused on manufacturing process improvements, shortening the time between data generation at the network edge, and AI-driven instructions for optimizing equipment performance in response to changing needs.

Investors are taking notice. Confluent’s successful first day of trading is one testament. So is the $15.5 million that Vectorized raised in its seed and Series A funding rounds led by Lightspeed Venture Partners and Google Ventures.

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