Getting Started with Snowflake Postgres
Snowflake Postgres is a fully managed PostgreSQL service built into the Snowflake platform. It gives you 100% Postgres compatibility — your existing applications, ORMs, drivers, and extensions work without code changes — while eliminating the operational burden of running Postgres yourself.
Unlike standalone managed Postgres offerings, Snowflake Postgres is natively connected to the Snowflake data platform. That means your transactional data is immediately available for analytics, AI, and collaboration without building ETL pipelines or managing data movement.
Why Snowflake Postgres?
- Managed operations — No patching, no vacuum tuning, no replica promotion runbooks. Snowflake handles infrastructure, HA, backups, and scaling.
- Real Postgres — Standard Postgres wire protocol, SQL syntax, extensions, and ecosystem compatibility. If it works on Postgres, it works here.
- Built-in analytics bridge — pg_lake syncs your Postgres tables to Snowflake as Iceberg tables, giving you warehouse-scale analytics on live transactional data.
- Cortex AI integration — Run LLM functions, build RAG pipelines, and create AI agents that reason over your Postgres data — no data movement required.
- One platform — Consolidate Postgres, analytics, AI, and app development on a single platform with unified governance and billing.
Key Capabilities
Instance Management
| Feature | Details |
|---|---|
| Postgres versions | 16, 17, 18+ |
| Cloud regions | AWS and Azure (expanding) |
| High availability | Automated replication and failover |
| Point-in-time recovery (PITR) | Restore to any point within a 10-day retention window |
| Replicas | Read replicas for scaling read traffic and offloading analytics |
| Mirror data | Mirror Postgres data to Snowflake for analytics, AI, and cross-platform queries via pg_lake |
| Scaling | Resize compute on demand without downtime |
| Networking | Network policies, PrivateLink, and VPC peering for secure connectivity |
Connectivity
Snowflake Postgres uses the standard Postgres wire protocol on port 5432. Connect with any tool in the Postgres ecosystem:
- CLIs — psql, pgcli
- GUIs — pgAdmin, DBeaver, DataGrip, Postico
- ORMs — SQLAlchemy, Django ORM, ActiveRecord, Prisma, Drizzle
- Drivers — libpq, psycopg, node-postgres, JDBC, Go pq
- BI tools — Tableau, Power BI, Metabase, Grafana
pg_lake: Postgres Meets the Lakehouse
pg_lake is the bridge between your transactional Postgres data and Snowflake's analytics engine. It continuously syncs designated tables to Snowflake as Iceberg tables, giving you:
- Warehouse-scale analytics without impacting your Postgres OLTP performance
- Cross-database joins between Postgres data and your existing Snowflake tables
- A foundation for Cortex AI — run LLM functions and build agents over your Postgres data
Extensions
Snowflake Postgres supports popular Postgres extensions including:
- pgvector — Vector similarity search for AI/ML embeddings
- PostGIS — Geospatial data types and functions
- pg_stat_statements — Query performance monitoring
- age — Apache AGE cypher graphing
Get a Snowflake Account
If you don't already have a Snowflake account, sign up for a free trial:
- Go to signup.snowflake.com
- Choose your cloud provider and region
- Complete the registration form
- Activate your account from the confirmation email
The trial gives you $400 in free credits and full access to Snowflake features, including Snowflake Postgres.
aside positive No credit card is required for the trial. You get 30 days or $400 in credits (whichever comes first) to explore the platform.
Your First Instance
Once you have a Snowflake account, launching a Postgres instance takes a few clicks in Snowsight:
- Navigate to the Postgres section in Snowsight
- Click Create Instance
- Choose your instance size, Postgres version, and region
- Set a network policy for access control
- Click Create — your instance will be ready in minutes
From there, connect with psql or your preferred client using the connection details shown in Snowsight.
For a complete hands-on walkthrough — creating an instance, connecting, loading data, and exploring platform features — follow the quickstart guide:
Step-by-step guide to launch your first instance and explore the platform.
What to Explore Next
Once your instance is running, here's where to go from here:
- Migrating to Snowflake Postgres — Move an existing Postgres database to the platform
- pg_lake — Set up analytics sync between Postgres and Snowflake
- Cortex AI Integration — Build AI-powered applications on your Postgres data
- Monitoring & Observability — Track instance health and query performance
- Connection Management — Optimize client connections and pooling
Conclusion
Snowflake Postgres gives you the Postgres you know — with the operational simplicity and platform capabilities of Snowflake behind it. Start with a free trial, follow the quickstart, and see how managed Postgres fits into your data platform.
Related Resources
Complete documentation for configuration, management, and features.
Hands-on quickstart: create an instance, connect, load data, and explore.
Sign up for a free Snowflake account with $400 in credits.
This content is provided as is, and is not maintained on an ongoing basis. It may be out of date with current Snowflake instances
