batch Twilio to Bigquery in minutes
Twilio is a versatile digital communications platform that allows developers to programmatically manage marketing, calls, email, messaging, and more. This connector allows you to sync data related to users accounts, records of various channels of communication, alerts, and more using the Twilio API.
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 integrates with an ecosystem of free, open-source connectors to extract data from Twilio with low latency, allowing you to replicate that data to various systems for both analytic and operational purposes. Twilio data can be organized into a data lake or loaded into other data warehouses or streaming 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
Twilio to Bigquery in minutes with millisecond latency.
Estuary helps move data fromTwilio 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.