DataCater's interactive pipeline designer allows building streaming data pipelines without coding. It ships an extensive repository of transformation and filter functions that cover most needs in data preparation for machine learning and analytics.
When you build data pipelines, the pipeline designer interactively previews their impact on the consumed data source, which creates full transparency on applied transformations.
Many transformation and filter functions
No coding required
Powerful data profiler
DataCater provides connectors for many different data stores, ranging from database systems over flat files and file systems to search indices. Data connectors are technically based on the Kafka Connect framework, which prevents vendor lock-in and enables you to develop custom connectors.
DataCater can continuously stream data changes from data sources to data sinks and transform them on the way, in real time.
Full automation of data preparation
Change data capture
Support for custom connectors
DataCater compiles data pipelines to highly-optimized Kafka Streams applications, which can be deployed with Docker or Kubernetes.
DataCater supervises executed pipelines, collects essential metrics that provide helpful insights into applied data transformations, and sends alerts once failures have been detected.
Kafka Streams applications
Continuous execution of data pipelines
Monitoring of pipeline health
DataCater continuously monitors the quality of all data sources and notifies you once changes have been discovered. This helps to identify flaws in the data as early as possible and enables you to adjust the consuming data pipelines to keep the quality of the data sinks at a high level.
Monitoring of quality metrics, such as the number of distinct values
Support for custom quality metrics