Full Stream Ahead! dA Platform is Generally Available and Ready for Download

March 28, 2018 | by Kostas Tzoumas

Today, we’re excited to announce that dA Platform, a production-ready stream processing infrastructure with open-source Apache Flink®, is generally available!

first unveiled dA Platform at Flink Forward Berlin 2017, and during the past few months, we’ve been running an early access program during which large-scale enterprises have been testing the product and providing us with feedback. And now we’re ready to share it with everyone else.

How can I get started with dA Platform?

A dA Platform trial sandbox VM is available at data-artisans.com/download. This is the easiest way to get started--we’ve taken care of the deployment environment and pre-deployed the platform so that you can be up and running in a matter of minutes.

Download dA Platform, a stream processing platform with open source Apache Flink
Already have access to a Kubernetes cluster and want to run the real thing? On our 
download page, we also offer a dA Platform trial that you can deploy on your own Kubernetes infrastructure. First, be sure to read the Kubernetes Trial Getting Started Guide in our documentation.

Want to learn more about dA Platform? You can...

dA Platform for stream processing - with Application Manager and open source Apache Flink

Why provide a complete stream processing infrastructure with Apache Flink®?

The mission behind dA Platform is the same now as it was when we first announced the product:

Today’s business reality is dominated by data–data that is produced continuously in the form of data streams.

We believe that the only way for enterprises to gain a meaningful business advantage from this data is through an architecture where services run continuously and can react immediately to important events. Gone are the days of waiting for hours for a computation to finish while competitors are already taking advantage of insights derived from their real-time data.

Building Apache Flink applications to model complex business logic has become relatively easy, as Flink’s APIs have evolved significantly since the project’s inception. But as we’ve mentioned before, we know that there’s still much work to be done to make stateful stream processing applications as easy as possible for anyone to deploy and manage.

Working closely with a wide variety of Flink production users has convinced us that operationalizing and supporting 24/7 stateful stream processing applications is a process that can be made easier. We have distilled that experience into a platform that addresses the shortcomings of  existing operations technologies, which are generally designed for stateless applications, and builds a powerful foundation for stateful real-time applications.

Get In Touch

Want to speak with someone on our team? Just fill at the form at the bottom of the download page, and we’ll follow up with you as quickly as possible.

We look forward to your feedback!  

Topics: Ververica Platform

Kostas Tzoumas
Article by:

Kostas Tzoumas

Related articles


Sign up for Monthly Blog Notifications

Please send me updates about products and services of Ververica via my e-mail address. Ververica will process my personal data in accordance with the Ververica Privacy Policy.

Our Latest Blogs

by Nico Kruber May 11, 2021

SQL Query Optimization with Ververica Platform 2.4

In my last blog post, Simplifying Ververica Platform SQL Analytics with UDFs, I showed how easy it is to get started with SQL analytics on Ververica Platform and leverage the power of user-defined...

Read More
by Jun Qin March 29, 2021

The Impact of Disks on RocksDB State Backend in Flink: A Case Study

As covered in a recent blog post, RocksDB is a state backend in Flink that allows a job to have state larger than the amount of available memory as the state backend can spill state to local disk....

Read More
by Konstantin Knauf March 10, 2021

Announcing Ververica Platform 2.4

Newest release adds full support for Flink SQL and Flink 1.12, and improves resource utilization via new shared session clusters.

Read More