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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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,
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.
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.
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.
One of the omnipresent challenges of building a product from scratch is you don’t initially know exactly how customers will want to use it. You build the product you would want to use and are passionate about, however, you must also listen to customers as you evolve your product to deliver exactly what they really […]
Since we first opened the doors at Eventador.io, customers have been building applications that make use of Apache Kafka for a wide variety of streaming data use cases. Over time, it became clear we were only solving for one part of the complete picture. With Kafka, our service had the data transport, durability, and scalability, […]
Over the past two decades I have witnessed many massive shifts in the data technologies landscape. I have seen a maturity of the RDBMS market, the adoption of NoSQL technologies, and organizations of every size struggling with data management in one way or another. Throughout all of this change, one area is starting to become […]