Connecting Your PostgreSQL & Presto Data
Whether you’re integrating PostgreSQL with Presto or moving data from one of these solutions to the other, getting your information where it needs to be is crucial. Use StarfishETL’s robust iPaaS to connect your data with speed and flexibility.
Secure Connections Between PostgreSQL to Presto
The iPaaS powering your PostgreSQL and Presto connection not only provides unrivaled scalability, but also offers strict security protocols to keep data safe as it moves across applications. StarfishETL applies two-fold data security between Amazon Web and our internal servers to maintain the highest levels of protected infrastructure. Strict data encryption practices and progressive security principles keep sensitive information secure at all times as it passes between PostgreSQL and Presto.
PostgreSQL and Presto Integration
Integrate PostgreSQL and Presto to boost your analytical power, align your teams, and create more omnichannel experiences across your business. StarfishETL makes the process seamless with a library of pre-configured maps at your fingertips and easy ways to customize your project. Check out the visual below to learn how a typical integration flows. Then, contact our team to request a quote on your PostgreSQL and Presto project.
Set up access to each system
Define processes & stages
Modify integration & add custom fields
Test integration
Run initial data migration load
Ensure keys are matching between systems
Start integration
About These Solutions
PostgreSQL is an open-source object relational database built for SQL compliance. PostgreSQL provides a scalable infrastructure that is reliable and highly responsive, an excellent platform for data warehousing and application development.
Presto is also known as PrestoDB and is an open source, distributed SQL query engine for big data. PrestoDB runs interactive analytic queries for large-scale analytics workloads across multiple sources such as Hadoop, MySQL, AWS S3, Cassandra, and Hive. This query engine is widely adopted for data lake analytics.