Every enterprise operates in two realms: one for real-time applications that process orders and engage customers, and another for analytics platforms that extract insights and drive AI. Snowflake is introducing Snowflake Postgres to bridge these realms with two key features:
1. Data mirroring, which is an always-on replication feature between Postgres and Snowflake, set to enter public preview soon.
2. Postgres for data lakes, allowing synchronization with analytics using open formats like Iceberg, which will be generally available shortly.
These features aim to simplify the connection between transactional and analytical data, reducing the need for complex ETL pipelines. Customer feedback indicates that transferring data between OLTP and OLAP databases is the most challenging infrastructure task, leading to costs and issues such as data inconsistencies and delayed decision-making. Snowflake Postgres offers a simplified integration method with low-latency data mirroring that automatically maintains target tables in Snowflake to reflect the current state of source tables in Postgres. This setup can be configured easily through various interfaces or a single SQL command.