After performing an initial snapshot of the data source, DataCater streams change events (INSERTs, UPDATEs, and DELETEs) to data sinks in real-time.
DataCater does not only improve the robustness and resource consumption of your data architecture, but also allows downstream applications to always work with current data.
Example: Stream data from Magento to a Snowflake data warehouse.
View our integrations
Use DataCater's Pipeline Designer to interactively build and deploy production-grade streaming data pipelines in a few minutes, without wasting time on manual programming or repetitive work.
DataCater can transform, clean, filter, and enrich data while streaming them from data sources to data sinks.
Choose from 35+ pre-defined transformations or write custom Python-based transformation functions.
Example: Anonymize customer data before loading them into a data warehouse.
DataCater is based on the industry standard for the streaming of event data: Apache Kafka, Apache Kafka Connect, and Apache Kafka Streams.
Deploy DataCater on new or existing Apache Kafka installations. On your premises or the cloud platform of your choice.
Use our DataCater Cloud offering, where we take care of all operations.
We care about your data.
Each pipeline is executed as an isolated container, preventing any unauthorized access.
We support on-premise installations, without requiring any connection to the internet.
DataCater integrates into existing monitoring solutions to ensure worry-free operations.
DataCater enables GDPR-compliant operations of streaming data pipelines.
We are proud that market-leading enterprises use DataCater for working with streaming data pipelines.
We would be happy to show you DataCater in action.
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Amazon RDS
Apache Kafka
HDFS
Wordpress
MongoDB
Elasticsearch
Google Cloud BigQuery
TYPO3
Magento
Microsoft SQL Server
MySQL
Oracle
Apache Solr
PostgreSQL
Shopware
HubSpot
Neo4j
Salesforce
Snowflake
Typeform
Zendesk