What is Continuous SQL? Stream Processing with Continuous SQL Explained.
It has become clear that streaming or real-time data has more value than data at rest. Continuous SQL enables organizations to deliver on the promise of, and handle the pressures of, streaming data.
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Top 3 Reasons Why Kafka + SQL is an Amazing Combination
The combination of Kafka and SQL can be a game-changer for your business. It simplifies streaming deployments, accelerates streaming app time-to-market, and helps you to unlock increased value from your Kafka deployment.
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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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The Growth of Self Service Streaming Platforms and Flink SQL at Flink Forward Berlin
Companies increasingly understand how critical streaming data is to success and are looking for better, more self service ways to democratize streaming data across their organization.
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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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Introducing SQLStreamBuilder
Today, we are launching SQLStreamBuilder (SSB): an interface to declare stream processing jobs using SQL. SQLStreamBuilder provides a powerful interface for writing SQL as well as managing SQL jobs.
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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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A 2018 Year In Review: Massive Growth And Exciting Moves
With 2018 wrapping up, I wanted to talk a bit about this last year. This year, and the massive growth we’ve enjoyed, has been a rollercoaster of the best kind for the entire team.
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The Flink Table And SQL API With Apache Flink 1.6
Learn more about what (awesome) changes Flink 1.6 brought to the Flink table and SQL API with a step-by-step guide for using them.
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The New System Of Record
The defacto system-of-record for the enterprise is moving to a distributed log architecture, and the movement is well underway.
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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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