Performance & Scalability

Managing growth stress-free

One of the biggest challenges in businesses is how to deal with growth. We understand the dynamic nature of constant IT adjustments to fulfill business needs. Having a flexible IT architecture to provide sufficient processing power and space would facilitate the demands encountered in today's business world.

With the CloverETL Server and Cluster, you have the option to scale proportionally with the need for increased capabilities.

CloverETL is based on an inherently parallel concept. If you add raw processing power by either increasing the number of cores or adding more IO channels, CloverETL can immediately utilize it and process data faster. The same transformation design can be used on desktop with small amount of data or can be moved to the Server or even the Cluster without needing to change anything. The transformation job is automatically optimized for the deployed platform.

Clover lets you start small and grow big
Start with the Designer on a Desktop

Nowadays, even a desktop computer or laptop is powerful enough to process a couple of million data records. Though not the most robust of our solutions, for small projects or one-time jobs, the CloverETL Designer on its own might be all you need.

Add the Server

Adding the CloverETL Server gives you extra processing power and increased robustness, as well as automation options. Multi-user access and even multi-tenancy is also supported. Having real-time processing needs? The CloverETL Server supports that.

Configure Cluster

When you need even more performance, setting up the CloverETL Cluster can speed things up. Allowing you to distribute the execution of jobs among individual nodes of the cluster or take one job and let multiple nodes participate on its execution, the CloverETL Cluster achieves a true data parallelization.

The Cluster also increases the overall robustness, as the failure of one node does not paralyze the whole system.

The Cluster also allows dynamic provisioning of worker nodes depending on the intended workload, allowing you to save costs and energy.

Learn more

CloverETL Cluster

Get more information on the CloverETL Cluster
solution for massive data processing