batch Microsoft Azure Blob Storage to Bigquery in minutes
Microsoft Azure Blob Storage is an object storage service offered by Microsoft. It's a cost-effective, durable, and elastic resource, making it easy to store data in the cloud. Azure Blob Storage lets you organize your data into "buckets" and provision access, so you can share data quickly, easily, and safely.
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 builds free, open-source connectors to extract data from Microsoft Azure Blob Storage as soon as it arrives, allowing you to easily create always-up-to-date copies of that data across your systems.
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.
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Estuary helps move data from
Microsoft Azure Blob Storage to Bigquery in minutes with millisecond latency.
Estuary helps move data fromMicrosoft Azure Blob Storage to Bigquery 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.