Views, streamed into Snowflake.
Send any Basalt view to a Snowflake table. Rows arrive through Snowpipe Streaming in seconds, with no warehouse running for the load.
Overview
How it works.
Basalt opens a Snowpipe Streaming channel per view partition and writes rows with offset tokens. Snowflake commits each batch with its token, so a restart resumes from the last committed row with no duplicates.
Setup
Set it up in three steps.
01
Add the destination
Create a user with key-pair auth and a role that can insert into the target schema. Basalt creates the table from the view's types.
# stream the revenue view into Snowflake basalt sink add revenue --snowflake ANALYTICS.PUBLIC --view revenue_by_min
✓ table REVENUE_BY_MIN created · 8 columns
✓ 4 channels open · end-to-end 2.3 s
02
Shape it with a view
Write plain SQL over the source. Basalt keeps the view current with every record and tracks lineage back to the topic, partition and offset.
CREATE MATERIALIZED VIEW revenue_by_min AS SELECT date_trunc('minute', ts) AS minute, currency, sum(amount) AS revenue, count(*) AS payments FROM payments WHERE status = 'captured' GROUP BY 1, 2;
03
Read it from anywhere
Every view is an endpoint the moment it exists. Call it over REST, connect with any Postgres client, or use the SDK from your app.
curl https://api.basalt.dev/v1/views/revenue_by_min?limit=5 \ -H "Authorization: Bearer $BASALT_TOKEN"
✓ 200 OK · 5 rows · served from eu-north-1 in 3.1 ms
Included
What you get.
01
Offset tokens
Each channel commits with a token, so a retry never writes the same row twice.
02
No warehouse load
Snowpipe Streaming writes rows directly. You pay for storage, not a running warehouse.
03
Typed tables
Columns map to NUMBER, VARCHAR, TIMESTAMP_TZ and VARIANT from the view schema.
04
Keyed merges
Keyed views can merge into a target table on a schedule as short as one minute.
Related
