Welcome

Welcome to the real-time, cloud-native data pipeline platform where data and developer teams unlock the full value of their data.
DataCater is a simple yet powerful approach to building cloud-native, real-time data pipelines. Our users report that DataCater saves 40% of their time spent on crafting data pipelines and helps them to go from zero to production in a matter of minutes.
For building data pipelines, you can choose from an extensive repository of pre-defined filter and transform functions, or code your own transforms in Python to build streaming data pipelines.
Features
Interactive development:
DataCater's pipeline designer allows iterating on data pipelines in seconds and deploying them in minutes. Let us take care of the complexity of data pipelines, so you can focus on your job.
Change data capture:
Plug-and-play connectors for change data capture (CDC) allow to consume data change events from a plethora of different data systems, e.g., databases, HTTP APIs, file systems, without implementing any custom code.
Real-time data processing:
DataCater compiles your pipelines to production-grade streaming applications, which can process data in real-time.
Powerful transformations:
Our first-in-class approach to transformations combines the efficiency of a no-code solution with the power of Python transformations. Implement any data preparation requirement in seconds to minutes.
Cloud native:
Being built for the cloud era, DataCater Self-Managed natively integrates with your private or public cloud platform and can be operated on your Kubernetes cluster.
Project-based collaboration:
Unlock the full potential of your team by collaborating on data pipelines.
Monitoring & notifications:
We continuously monitor the health of connectors and data pipelines and can notify you via e-mail or Slack when something goes wrong. On top of that, DataCater Self-Managed offers Prometheus metrics endpoints that you can integrate
Logging:
Access the logs of your data pipelines through our UI or API to watch transformations being applied to data on the event level and investigate potential issues instantly.
Questions?
We are always happy to chat data streaming and help with any questions that you have. Please reach out to us at [email protected] or join our Community Slack.
Next - Introduction
Use Cases
Last modified 2mo ago