Normalizing JSON Data in Kafka Topics? SQLStreamBuilder Input Transforms to the Rescue

Input filters allow you to write a javascript function that operates on each message after it’s consumed from Kafka (or any other source) but before you write SQL against it.

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Javascript Functions in Flink with SQLStreamBuilder

Javascript Functions allow you to create arbitrary functions and call them directly from SQL. You con’t need to restart your system, stop your cluster, or compile/recompile anything. Just specify a function and get to business.

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Joining Kafka Streams Using SQL to Enrich and Route Data

Joins are an important and powerful part of the SQL language. You can perform joins in SQLStreamBuilder to enrich data and create net new streams of useful data.

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SQLStreamBuilder October Feature Update

Our mission has remained clear—to build the best way to create, manage stream processing jobs using SQL, so you can work with your Kafka clusters, databases, and processing logic like the databases you know.

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SQLStreamBuilder Feature Update

I thought I would share a couple of improvements and features we recently added to SQLStreamBuilder. If you aren’t familiar, SQLStreamBuilder allows you to run Streaming SQL jobs against streams of data—initially on Kafka.

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Apache Flink: Checkpoints And Savepoints

To understand the value of Apache Flink, it’s still important to know the difference between a checkpoint and a savepoint. These mechanisms for saving state are similar in design but used for two different purposes.

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What Does Fully Managed Really Mean?

As I’ve come on board at Eventador and gotten ramped up, one subject that stood out immediately as crucial to us and that we talk about in-depth, is the reality of our fully managed support.

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The Eventador Stream Processing Stack

Eventador allows you to quickly build and manage modern streaming data workflows on top of these state of the art platforms – Kafka and Flink.

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Kafka SASL Authentication

Core support for Simple Authentication and Security Layer (SASL) was added to Apache Kafka in the 0.10.2 release. We are excited to add this authentication mechanism to the Eventador service. Here is how it works.

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Apache Flink® On Eventador.Io

With the addition of Apache Flink – Eventador.io has a true end-to-end enterprise-grade stream processing platform. We run the complex infrastructure and provide support, you can focus on your streaming code.

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Announcing Apache Flink 1.3 On Eventador.Io (Beta)

Flink has become popular in recent years—a number of companies have started weaving it into their data backbones for critical line-of-business applications. We’ve had numerous discussions with customers about Flink. Our path became clear.

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0.9: Teams, Github, Plans And More

This release focuses on making the service even more robust, easier to use, and overall customer experience. Many of these features were inspired by direct feedback from you, our customers.

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0.8: PrestoDB & Eventador.io

Since the very first release of Eventador.io, we have had a SQL interface. We believe that SQL is an incredible language for dealing with streaming data and it opens up an ecosystem of utilities.

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0.7 Release And Looking Towards 1.0

Eventador 0.7 is out! We pushed a number of bug fixes and minor improvements that will make our platform more powerful and easy to use.

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