Comparing Apache Flink and Spark for Modern Stream Data Processing

Decodable supports AWS PrivateLink to securely bridge our platform with customer infrastructure operating in Amazon AWS.

Less than a decade ago, it was common to hear "We don’t do cloud. We don’t need it." Just as there were naysayers about the cloud, there are those who may proclaim, "We don’t do real-time. We don’t need it." But much like the cloud, the tide is turning, and the benefits of real-time data are becoming increasingly apparent.

The landscape of data infrastructure technology has witnessed a transformative shift as companies tap into new workloads to power real-time applications. Within this rapidly evolving ecosystem, navigating the myriad of service providers and solution offerings can be daunting. Our buyer's guide was created to help you select the right solution for your specific requirements.

Welcome to the Checkpoint Chronicle, a roundup for May 2024 of interesting stuff in the data and streaming space. Your hosts and esteemed curators of said content are Gunnar Morling and Robin Moffatt.

In this blog post I’m going to show you how to set up such a real-time streaming pipeline between MySQL as a system of record and OpenSearch as a derived data store, enabling use cases such as full-text search and dashboarding.

Welcome to the Checkpoint Chronicle, a roundup for April 2024 of interesting stuff in the data and streaming space. Your hosts and esteemed curators of said content are Gunnar Morling and Robin Moffatt.

Announcing the release of our multi-stream connector (MSC) feature at Decodable. With this new feature, you can unify multiple resources in a data system like a Postgres cluster under a single connection, yielding even greater reduction in cost and operational overhead. Read on for a deeper look at why multi-stream connectors are valuable, how we architected them, and see an example of how to use them.

As we embrace the spring season, we're excited to share with you our latest product updates. These new features enhance your experience with Decodable by boosting efficiency, broadening the support with the data ecosystem, and offering a cleaner, simpler way to manage how data moves through your stack.

A wondrous walk through some examples of troubleshooting Flink SQL. From ClassNotFoundException problems to S3 configuration and JDBC drivers, this blog post provides a valuable reference for understanding how to approach solving your next Flink SQL error message.