Kafka to Bigquery in minutes
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.
Google Bigquery is a cloud-based data warehouse that offers highly scalable and distributed SQL querying over large datasets. Using OLAP (Online Analytical Processing), Bigquery offers the ability to rapidly answer multi-dimensional analytic database queries with potentially large reporting views by breaking a query up between many worker nodes and reassembling the finalized answer.
Estuary helps move data from
Kafka to Bigquery in minutes with millisecond latency.
Estuary builds free, open-source connectors to extract data from Kafka in real-time, allowing you to offload data to various systems for both analytical and operational purposes. Kafka data exists in a stream and often benefits from being organized into a data lake or placed into a warehouse for analysis with history.
Data can then be directed to Bigquery using materializations that are also open-source. Connectors have the ability to keep warehouses as up-to-date as the warehouse can handle without incurring costs. This allowing Bigquery to receive data with under 10-second latency.