Decodable Arrives at Flink Forward With Updated Connectors, Talks on Autoscaling and Multi-Tenancy on Apache Flink®

Decodable Arrives at Flink Forward With Updated Connectors, Talks on Autoscaling and Multi-Tenancy on Apache Flink®

Company’s streaming data platform for real-time applications is built on Apache Flink

SAN FRANCISCO—August 1, 2022—FLINK FORWARD—Decodable, the real-time data engineering company, is bringing updated connectors and talks on using Flink at scale to Flink Forward, the Apache Flink Conference taking place this week in San Francisco. Apache Flink is an open source, unified stream-processing and batch-processing framework on which the Decodable platform is built.

“Part of our mission is to give back to the Flink community,” said Eric Sammer, CEO of Decodable. “Apache Flink is the best open source framework and distributed processing engine for real-time stream processing. It handles some of the most sophisticated workloads at in-memory speed and it’s proven at scale, powering some of the largest products and services in the market. That’s why we’ve built our platform atop Flink, and it’s why we’re contributing our improvements to several Flink connectors, making them more production-ready for various use cases.”

Examples of connectors improved and contributed to the project by the Decodable engineering team include S3 and a newly contributed Delta Lake connector, as well as various bug fixes to Flink.

Beyond connectors, Decodable works within the Flink community in other ways. The company hired Robert Metzger, committer and PMC chair of the Flink project. Metzger is focused on improving the deployment and operation experience of Flink, with a focus on autoscaling and generally working towards a cloud native Flink experience. Metzger previously co-founded and successfully exited Data Artisans (now Ververica), the company that originally created and commercialized Flink. He is a frequent speaker at conferences such as the QCon, ApacheCon and meetups around the world.

At the event, Metzger will discuss “Autoscaling Flink with Reactive Mode” on August 3 at 9:50 AM. Later that day, Sharon Xie will present “The Top 3 Challenges Running Multi-Tenant Flink at Scale” at 3:50 PM. Xie is a founding engineer at Decodable, leading the core platform team in building, maintaining and operating the Decodable platform.

About Decodable

Decodable’s mission is to make streaming data engineering easy. Decodable delivers the first real-time data engineering service—that anyone can run. As a serverless platform for real-time data ingestion, integration, analysis, and event-driven service development, Decodable eliminates the need for a large data team, clusters to set up, or complex code to

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