The developer-friendly ETL platform for transforming data in real-time

Powering teams at

Features of DataCater

Python® transforms

All transforms and filters, both pre-defined and user-defined functions, are developed in standard Python.

Interactive development

Use the interactive preview capabilities of our pipeline designer and API to iterate on streaming data pipelines in seconds.


You can easily share your filters and transforms with other developers and extend the transformation capabilities of DataCater.

Built for Apache Kafka®

DataCater natively integrates with Apache Kafka and can work with any product that is compatible with the Kafka API.

Plug & play connectors

Your data is not yet in a Kafka topic? Use our source and sink connectors for integrating external databases and APIs with your streams.

Integrates with Kubernetes®

DataCater deploys pipelines in Kubernetes, which allows you to benefit from elastic scalability and pipeline-level resource definitions.

What our customers say about us


"As a Data Engineer, I know how difficult it is to deploy a streaming solution. With DataCater it is made a lot simpler and without writing code. I don't have to worry about scaling and I can manage my pipelines with an easy-to-use online interface."

Dr. Nawar Halabi, Machine learning engineer

Case study with ING
MM New Media GmbH

"Traditionally being a publisher focussed on national and international headlines, was able to implement its first large-scale local news coverage thanks to the data-handling infrastructure provided by DataCater."

André Tschachtli, CTO

Case study with
Vitas GmbH

"After evaluating six providers, we chose DataCater and are extremely happy with the decision. We are able to build our pipelines with DataCater’s no-code pipeline designer in a tremendously short amount of time. Its support for Python transformations enables us to implement complex data transformations quickly and safely. We work with medical data and have high requirements with regards to data sovereignty that we can meet by operating DataCater on our own Kubernetes clusters."

Thomas Abend, CEO

Case study with
Xanevo GmbH

"Building data-driven products for our customers has become much quicker since using DataCater. Not only are we able to drastically reduce our time to product but the intuitive user interface allows us to re-allocate project resources on the fly."

Jan Kaiser, CEO

Faster data development

Users report that DataCater helps them to save around 40% of the time spent on working with data pipelines, while making a real-time, cloud-native data stack accessible.

Real-time data

DataCater enables you to deliver fresh and high-quality data to downstream consumers without having to become an expert in distributed computing. Say goodbye to working with outdated data.

Cloud-native data

DataCater has been built for the cloud era. We run on top of Kubernetes and perfectly integrate into a cloud-based data architecture.

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