UPDATED 07:00 EDT / MARCH 30 2016

NEWS

Apache Flink creators snag $6M for stream-processing startup

Just when you thought you had finally wrapped your brain around the importance of Apache Spark for event processing, there’s a new real-time player to consider.

Data Artisans, a startup founded by the original creators of the Apache Flink stream data processing framework, is today announcing Series A funding of $6 million to develop analytics products based on Flink. This brings the company’s total funding to $7.3 million and goes a long way toward establishing Flink as a major new force in data analytics.

The latest round was led by Intel Capital Corp. with participation from Tengelmann Ventures Management GmbH as well as existing investor b-to-v Partners AG. Intel Capital Director Erik Jorgensen will join Data Artisans’ board.

Stream processing is the latest craze to hit the big data analytics market. Apache Spark lit things up last year with a major endorsement from IBM, which said it will embed Spark into all of its analytics and ecommerce platforms and commit more than 3,500 researchers and developers to work on Spark-related projects. Spark has also received important endorsements from all of the big three Hadoop players: Cloudera Inc., MapR Technologies Inc. and, most recently, Hortonworks Inc.  Databricks Inc., which is the leading commercial entity behind Spark, has raised $47 million in venture funding.

Flink isn’t technically a competitor to Spark, but some people say it is. Like Spark, Flink is an in-memory processing engine, which makes it very fast. However, Flink was designed to process streaming data in real time whereas Spark’s roots are as a batch processor. Spark has been steadily acquiring more real-time features over the past year, but its approach to real-time processing is sometimes described as “micro-batching,” or processing small amounts of batch information quickly, whereas Flink is pure real-time.

The differences may be academic in many cases, but in applications involving continuous monitoring of data streams for instantaneous decision-making, Flink has the edge. Both frameworks work with a wide variety of file systems and programming languages.

“Flink has attracted a lot of attention over the past 12 to 18 months for tackling a lot the streaming analytics usage scenarios that Spark is still working to solve,” said George Gilbert, Wikibon’s big data analyst. “Data Artisans is still very early in their product maturity, but another funding round should help them build out their go-to-market capability and reassure prospective customers that they have the resources to persevere.”

Flink marked a milestone of sorts three weeks ago with the release of version 1.0.0, which features guaranteed backward compatibility with applications written to the Flink application program interfaces (APIs) going forward. This stability promise is important for corporate adoption.

And corporations are climbing on board. Enterprises that are putting the framework through its paces include Capital One Financial Corp., LM Ericsson Telefon AB, Amadeus IT Holding SA, ResearchGate GmbH, and King.com Ltd. Data Artisans said Flink is among the top five Apache big data-related projects, with more than 150 contributors and more than 25 local user groups.


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