Warehouse

Your data stack starts here. Every pipeline, transformation, and dashboard feeds into a warehouse. Getting this decision wrong costs you a painful migration 18 months later. Getting it right means the rest of your stack falls into place. The three serious options for startups are Snowflake, BigQuery, and Redshift. Databricks is worth knowing about but overkill until you have a data engineering team. The three options Snowflake Snowflake is the default for a reason. It works with any cloud, separates compute from storage (so you only pay for queries when they run), and has the broadest connector and tool support in the ecosystem. dbt, Fivetran, Airbyte, Looker, Tableau — everything integrates with Snowflake first. ...

What Snowflake Is Snowflake is a cloud data warehouse built on a multi-cluster shared-data architecture. Storage and compute are separated: your data lives in cloud object storage (S3, GCS, or Azure Blob), and Virtual Warehouses — independently sized compute clusters — query it on demand. You can scale compute up or down, or suspend it entirely, without touching your data. It runs on AWS, Azure, and GCP but Snowflake manages every layer; you never touch infrastructure. ...