batch Redshift to PostgreSQL in minutes
Amazon Redshift is a massively scalable cloud data warehouse that is part of the larger AWS platform. It is an OLAP-style database that employs Massively Parallel Processing (MPP) technology to handly exabyte-scale data. The Redshift connector allows you to integrate data from your warehouse by leveraging the Redshift JDBC driver provided by Amazon.
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 Redshift with low latency, allowing you to replicate that data to various systems for both analytic and operational purposes. The Redshift 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.
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Estuary helps move data from
Redshift to PostgreSQL in minutes with millisecond latency.
Estuary helps move data fromRedshift to PostgreSQL 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.