batch Microsoft Dynamics Customer Engagement to Kafka in minutes
Microsoft Dynamics Customer Engagement is an enterprise resource planning app from Microsoft. The product is part of the Microsoft Dynamics family and helps Customer Relationship Management (CRM) for SMB companies.
Apache Kafka is a popular open-sourced event-streaming platform.
It’s focused on allowing enterprises to use real-time data as the backbone of their operations. Kafka provides an event-based backbone for many Fortune 500 companies.
Estuary integrates with an ecosystem of free, open-source connectors to extract data from Microsoft Dynamics Customer Engagement with low latency, allowing you to replicate that data to various systems for both analytic and operational purposes. Microsoft Dynamics Customer Engagement data can be organized into a data lake or loaded into warehouses, databases, or streaming systems. Microsoft Dynamics Customer Engagement runs on a MySQL database and you can use the MySQL connector to connect to any Microsoft Dynamics family source.
Data can then be directed to Kafka using materializations that are also open-source, streaming to Kafka with millisecond latency.
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Estuary helps move data from
Microsoft Dynamics Customer Engagement to Kafka in minutes with millisecond latency.
Estuary helps move data fromMicrosoft Dynamics Customer Engagement to Kafka in minutes with millisecond latency.
Estuary enables the first fully managed ELT service that combines both millisecond-latency and point-and-click simplicity. Flow empowers customers to analyze and act on both historical and real-time data across their analytics and operational systems for a truly unified and up-to-date view.
Flow is developed in the open and utilizes open source connectors that are compatible with a community standard. By making connectors interchangeable with other systems, the Estuary team hopes to expand the ecosystem for everyone’s benefit, empowering organizations of all sizes to build frictionless data pipelines, regardless of their existing data stack.