Migration
Vertica to Snowflake migration: a practical guide
How to migrate Vertica to Snowflake: exporting to Parquet and loading with COPY INTO, replacing projections, flex tables to VARIANT, rewriting TIMESERIES with time spines and ASOF JOIN, UDx and in-database ML.
Hemant Walchale
· 2 min read
Vertica serves many event, telemetry and marketing analytics workloads. Teams move to Snowflake to stop managing nodes, projections and resource pools, and to get elastic compute per workload. Most Vertica SQL converts easily; time-series syntax, flex tables and extensions need deliberate rewrites.
This is the approach we recommend.
1. Inventory
List schemas, tables, projections, flex tables, views, UDx, COPY load jobs, ML models, resource pools, schedules and consumers. query_requests and projection_usage show what is queried. Archive the rest.
2. Map Vertica to Snowflake
| Vertica | On Snowflake |
|---|---|
| Tables | Snowflake tables |
Projections (ORDER BY, SEGMENTED BY) |
Removed; optional clustering keys |
| Flex tables | VARIANT columns |
COPY from files |
Stages with COPY INTO, Snowpipe |
EXPORT TO PARQUET |
The path for historical data |
TIMESERIES, gap filling, interpolation |
Time spine with GENERATOR, joins, window functions, ASOF JOIN |
| Analytic functions | Window functions |
| UDx (C++, Java, Python, R) | SQL, Python, Java or JavaScript UDFs |
| In-database ML | Snowpark Python, or Cortex ML functions for common forecasting and anomaly tasks |
| Resource pools | Separate virtual warehouses per workload |
| Roles and grants | Role-based access control, masking and row access policies |
3. Convert SQL
Most queries convert with small changes. Test date and time functions, INTERVAL arithmetic, string functions, LIMIT ... OVER patterns and implicit casts, then rewrite time-series queries using the patterns above.
4. Move data and reconcile
Export each table to Parquet on cloud storage, load it with COPY INTO, and keep tables in sync from upstream sources during the parallel run. Compare every table by domain; event data needs special care with timestamp precision and time zones.
5. Shrink and retire
Remove Vertica nodes as domains move and stop renewing licence capacity after the final cutover.
The short version
Export to Parquet and load with COPY INTO, drop projections, move flex tables to VARIANT, rewrite TIMESERIES with time spines and ASOF JOIN, convert UDx and ML to Snowflake functions and Snowpark, separate warehouses per workload, reconcile and retire nodes by domain.
Compare with Vertica to Databricks, or browse all migration guides.
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