Resources

451 Research Brief

The complexity of establishing and maintaining stream processing architectures is widely acknowledged. As the costs of real-time data have become less prohibitive, skillsets are increasingly the bottleneck to leveraging the technology. Decodable is seeking to address this bottleneck directly by letting teams establish capabilities that can filter, route, enrich or transform data streams using SQL, and easily build streaming applications.

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Achieve Results Faster with Apache Flink SQL

Flink SQL provides the ability to process real-time data using Structured Query Language, the de facto standard language used to access and process data, and one that is familiar to a very wide range of developers. It provides an optimized implementation that is difficult to achieve with Java, resulting in the clear advantage of being able get to market faster with efficient real-time applications when using Flink SQL.

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Video & Podcasts

Change Data Capture With Apache Flink

In this interview, we talk about Change Data Capture with Debezium and Flink with experts in this field as our guests: Gunnar Morling, one of the creators of the Debezium project answers any about CDC in general, as well as Debezium-specific questions. For deep insights into the Flink CDC Connectors project, we have Leonard Xu and Jark Wu, two long-term Flink contributors and leads on the Flink CDC project. Robert Metzger, the PMC Chair of the Apache Flink project asks the questions.

Video & Podcasts

Realtime ETL is Easier Than You Think

In this demo-heavy webinar you'll learn why streaming ETL is essential for modern businesses, why current batch architectures with monolithic data warehouses are out of date and how Decodable is approaching the challenges traditionally associated with Streaming ETL.

Video & Podcasts

What's new in Apache Flink 1.16

Apache Flink PMC Chair Robert Metzger summarizes the top features shipped in the latest Apache Flink 1.16 release. Official Flink release announcement: https://flink.apache.org/news/2022/10/28/1.16-announcement.html Slides: https://speakerdeck.com/rmetzger/whats-new-in-flink-1-dot-16 Chapters: 0:00 Introduction 0:17 SQL Gateway 1:36 Hive Compatibility 2:15 Changelog State Backend 4:30 Overdraft Buffers and Unaligned Checkpoints 6:55 RocksDB 7:43 Lookup Joins & Async I/O 9:23 Batch Improvements 12:12 Wrap Up

Video & Podcasts

Machine Learning with Apache Flink

Robert Metzger, Software Engineer at decodable and PMC member of Apache Flink asks the questions. We talk about the machine learning space in general, relevant machine learning projects for Apache Flink and Apache Flink ML itself: What’s the status of the project right now, and what are the plans for the future.

Video & Podcasts

Top 3 Challenges Running Multitenant Flink At Scale

In this talk, originally given at Flink Forward 2022, Decodable founding engineer Sharon Xie explores the key challenges and solutions building a managed Apache Flink solution into the Decodable stream processing platform.

Tutorial

Building A Stream Processing Pipeline With SQL

In this demo video Charles Harding builds a stream processing pipeline with SQL using Decodable in under 8 minutes, showing the developer experience, SQL editor and preview function for testing the SQL transformation.

Video & Podcasts

Benefits of Real-Time Stream Processing

Join David Fabritius as he explores the features and benefits of leveraging Decodable for your real-time stream processing needs. Decodable is a stream processing platform providing the simplest method for moving data anywhere with real-time speed, transformed to match the needs of its destination. As a fully managed stream processing service, Decodable provides pre-built connectors to external systems and leverages SQL to provide a familiar development experience so you can be up and running in minutes, not months.

Tutorial

Getting Started with Decodable

This quick introductory tutorial walks you through creating your first data flow in Decodable. Create a free account at https://app.decodable.co/ Run this demo for yourself by following the tutorial (includes all SQL in this video): https://docs.decodable.co/docs/web-quickstart-guide

Analyst Report

451 Research Brief

The complexity of establishing and maintaining stream processing architectures is widely acknowledged. As the costs of real-time data have become less prohibitive, skillsets are increasingly the bottleneck to leveraging the technology. Decodable is seeking to address this bottleneck directly by letting teams establish capabilities that can filter, route, enrich or transform data streams using SQL, and easily build streaming applications.

Video & Podcasts

Building a practical real-time data platform for everyone

Decodable's CEO, Eric Sammer, explores the challenges faced building a real-time streaming data platform and how Decodable has solved them.

Video & Podcasts

PODCAST: Stream Processing, Observability, and the User Experience with Eric Sammer

Eric Sammer joins host Sam Ramji on the Open || Source || Data podcast.

News

The New Stack: Apache Flink for Unbounded Data Streams

Eric Sammer explains what Apache Flink is and why Booking.com, Pinterest, Stripe, Alibaba and Goldman Sachs are just a few of the companies that rely on Flink.

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