We are rapidly adding features and iterating on SQLStreamBuilder, I thought I would share a couple of improvements and features we recently added. If you aren’t familiar, SQLStreamBuilder allows you to run Streaming SQL jobs against streams of data—initially focused on Apache Kafka. Here is my blog post introducing SQLStreamBuilder, check it out for some […]
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‘Apache Flink’ Category
SQLStreamBuilder allows you to declare stateful stream processors using SQL. It is massively scalable, fault tolerant and production grade. Using SQL to build streaming jobs allows for a new level of simplicity and power and makes building and managing complete stream processing topologies easy and quick.
Over the last quarter, we invested heavily in building a Cloud Native version of the Eventador Platform on Kubernetes (K8s) – for both Fully Managed Apache Kafka and Fully Managed Apache Flink. Part of the reasoning for our focus on Kubernetes and containers was to enable the quick and seamless adoption of additional cloud platforms,
Arguably the most powerful feature of Apache Flink is its ability to do stateful computations on a boundless stream of data. Apache Flink is the core of Eventador’s Fully Managed Apache Flink stack. That said, to understand the value of Apache Flink, it’s still important to know the difference between a checkpoint and a savepoint. […]
With 2018 wrapping up, I wanted to take a few minutes (and inches of space here) to talk a bit about Eventador in this last year. This year, and the massive growth we’ve enjoyed, has been a rollercoaster of the best kind for the entire team.
I’m fresh off the plane from two back to back weeks in San Francisco – starting with the Kafka Summit 2018 and finishing up with Oracle OpenWorld. Two drastically different conferences, but they both reinforce our thinking and continue to bolster our opinion: The defacto system-of-record for the enterprise is moving to a distributed log […]
Streaming data is everywhere. IoT, high tech manufacturing, national security, smart cities, web log analysis, systems telemetry, AI and ML workflows, and a myriad of other modern use cases are driving this trend skyward.
While Twitter and WordCount are probably two of the most common ways to get started with streaming data, there’s good reason (for Twitter at least) – it’s a fun way to work on actual real-time, unbounded streams of interesting data. In this post, I’m going to explore some techniques to normalize, window, and introspect the […]