batch Square to PostgreSQL in minutes

Square

Square is a digital payment platform that makes it easy for businesses of all sizes to accept credit card payments through a mobile POS. This connector leverages the Square API to extract data related to customers, payments, tax, team members, and more.

PostgreSQL

PostgreSQL is one of the most powerful open source relational databases in the world. It’s developed a broad community in its 30-plus year history.

It features ACID transactions and is designed to handle a range of workloads from single machines to distributed architectures with replication.

Estuary integrates with an ecosystem of free, open-source connectors to extract data from Square with low latency, allowing you to replicate that data to various systems for both analytic and operational purposes. Square data can be organized into a data lake or loaded into other data warehouses or streaming systems.

Data can then be directed to Postgres using materializations that are also open-source. Connectors have the ability to keep databases as up to date as posible without incurring costs, allowing Postgres to be kept up to date with millisecond latency.

Talk to Estuary Today

Contact Us

Estuary helps move data from

Square to PostgreSQL in minutes with millisecond latency.

Estuary helps move data fromSquare to PostgreSQL in minutes with millisecond latency.

About Estuary

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.