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Snowflake alternative

Looking for an ecommerce analytics stack without Snowflake?

Discover how SourceMedium compares as an alternative to Snowflake for ecommerce analytics, attribution, and data management.

Common Snowflake pain points

Why teams look for a Snowflake alternative.

Warehouse costs that spiral

Credit-based pricing with 60-second minimum billing means even short dashboard queries get billed for a full minute. CFOs regularly discover Snowflake costs have grown 200–300% beyond expectations.

Five more tools required

Snowflake is only a warehouse. Add Fivetran ($1.5K–$3K/mo), dbt ($100–$500/mo), Looker ($3K–$10K/mo), reverse ETL ($500–$1.5K/mo), and a data engineer ($8K–$15K/mo) — total: $16K–$38K/month.

No ecommerce-specific features

No attribution, no LTV, no cohort analysis, no pre-built dashboards. Snowflake's retail resources target enterprise retailers (Kesko, John Lewis), not DTC brands.

How SourceMedium compares to Snowflake

A feature-by-feature comparison across the capabilities that matter most.

Feature
Integrations & Data Sources Commerce, ads, email, subscriptions, and ops — reconciled daily with 2,500+ automated quality checks No data loading included — requires Fivetran, Airbyte, or another ELT tool
Data Freshness Reconciled daily across all sources with full historical backfill — every metric traceable to its source Depends entirely on your ELT tool and orchestration setup
Attribution Models Server-side multi-touch attribution — no new pixels, works with your existing tracking infrastructure Not included — must be built from scratch or purchased separately
Cohort / CLTV 20 pre-built analytics modules including LTV, repurchase, retention, and new customer analysis — ready to use on day one Not included — must be modeled from scratch using SQL/dbt
Dashboards & Visualization Pre-built dashboards, forkable Looker Studio templates, and an AI analyst that answers questions with auditable SQL Not included — requires Looker ($3K–$10K/mo), Tableau, or another BI tool
Custom Metrics Define a metric once, use it everywhere — dashboards, SQL, and AI always return the same answer Must be defined and maintained by your data team in dbt or SQL views
SQL / Export / API Access Managed BigQuery warehouse with included compute and unlimited storage — any tool that supports BigQuery connects natively Full SQL warehouse — but credit-based pricing means cost scales with every query
Support & Success Dedicated US-based CSA, included quarterly solution hours, and structured roadmapping Ticket-based support; dedicated engineering resources required

Based on publicly available documentation, last verified February 2026.

Looking for a Snowflake alternative for ecommerce analytics?

If you're evaluating whether Snowflake is the right foundation for your ecommerce analytics, the real question isn't about Snowflake itself — it's about the five other tools and the engineer you need on top of it.

What to look for instead of a Snowflake-based stack

One product, not six. A data warehouse is just storage and compute. You still need connectors, transformation, dashboards, attribution, and analytics — each a separate vendor with separate pricing, support, and failure modes. Look for a platform that handles the full pipeline.

Predictable pricing, not credit-based billing. Credit-based pricing that scales with every query and spikes during seasonal peaks makes costs impossible to forecast. Your analytics bill shouldn't penalize you for asking more questions or growing revenue.

Ecommerce-specific analytics out of the box. Attribution, LTV, cohort analysis, contribution margin, and product analytics should work from day one — not require months of custom dbt modeling by a data engineer.

Time to value in days, not months. A Snowflake-based stack takes 6–12 months to produce its first useful insight. Ask any vendor: how long until my team is actually using this? And if we leave, what happens to our data, dashboards, and team's work?

How SourceMedium addresses these needs

SourceMedium replaces the entire Snowflake-based stack with one product. No credit monitoring, no warehouse sizing, no seasonal compute spikes during BFCM. You get a managed BigQuery warehouse with included compute, 2,500+ automated quality checks, and pre-built analytics modules that work from day one.

See also: SourceMedium vs. building an in-house data stack

See what ecommerce analytics looks like without the credits. Request a demo →

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