First Elephants, Now Whales: Big Data Integration in Docker Containers
It’s been an exciting year at Syncsort. Around this time last year we announced a Hadoop edition of our ETL product. A few months later, it was available on the cloud. Today we’re proud to announce Ironcluster ETL, Docker Edition; the packaging of our ETL product as a Docker container.
Never heard of Docker? This isn’t about pants.
Docker is an open source platform for developers and sysadmins to build, ship, and run applications.
Docker has the same concept as a container used for cargo ships: a standard container that is loaded with virtually any goods, and stays sealed until it reaches final delivery. In between, containers can be loaded and unloaded, stacked, transported efficiently over long distances, and transferred from one mode of transport to another.
Docker enables any payload to be encapsulated as a lightweight, portable, self-sufficient container that can be manipulated using standard operations and run consistently on different systems.
Docker containers are isolated, but share the Linux OS kernel, and where appropriate, bins/libraries. This results in significantly faster deployment, much less overhead, easier migration and faster performance. You share the host OS services, so unlike a Virtual Machine, you’re not replicating the OS. There is a lot more information on the Docker web site and a cool interactive tutorial as well here.
One of the common use cases for Docker is automating the packaging and deployment of applications, such as Syncsort’s ETL product.
Syncsort is offering our ETL product – Ironcluster ETL, Docker Edition – in the Docker Hub repository. You can now easily evaluate the Linux version of our ETL product by taking advantage of the portability of a Docker container. Whether deploying on a Linux server, virtual machine, or EC2 instance, it takes only seconds to get started. We call this the Ironcluster ETL, Docker Edition Test Drive; you can register to get your license key as well as access to other resources here.
And this is just the beginning. As Docker announces its first production-ready version, we’re looking forward to more exciting developments.