Modern Data Stack alternative
There's a better way than assembling a data stack
Discover how SourceMedium compares as an alternative to Modern Data Stack for ecommerce analytics, attribution, and data management.
Common Modern Data Stack pain points
Why teams look for a Modern Data Stack alternative.
$200K–$500K+/year total cost
Warehouse ($1.5K–$15K/mo) + ETL ($1K–$8K/mo) + dbt ($500–$7K/mo) + BI ($500–$12.5K/mo) + orchestration + reverse ETL + at least 0.5 FTE data engineer ($5K–$20K/mo). Year 1 costs exceed projections by 60% on average.
6–12 months to first useful insight
Months 1–2 for hiring, 3–4 for tool selection and setup, 5–8 for building ecommerce data models, 9–12 for dashboards and bug fixes. 53% of projects go 189% over their original budget.
85% failure rate for data projects
85% of data science projects never reach production (VentureBeat). Only 20% of analytic insights deliver business outcomes (Gartner). 68% of enterprise data goes entirely unused.
How SourceMedium compares to Modern Data Stack
A feature-by-feature comparison across the capabilities that matter most.
| Feature | MDS | |
|---|---|---|
| Integrations & Data Sources | Commerce, ads, email, subscriptions, and ops — reconciled daily with 2,500+ automated quality checks | Assemble yourself: warehouse + ETL + dbt + BI + reverse ETL + orchestration + observability = 6–8 tools minimum |
| Data Freshness | Reconciled daily across all sources with full historical backfill — every metric traceable to its source | Depends on your ETL, orchestration, and warehouse configuration — each a separate failure point |
| Attribution Models | Server-side multi-touch attribution — no new pixels, works with your existing tracking infrastructure | Must be built from scratch — typically months of custom development |
| Cohort / CLTV | 20 pre-built analytics modules including LTV, repurchase, retention, and new customer analysis — ready to use on day one | Must be modeled from scratch using dbt — Daasity calls this 'the longest and most complicated element' |
| Dashboards & Visualization | Pre-built dashboards, forkable Looker Studio templates, and an AI analyst that answers questions with auditable SQL | Requires separate BI tool (Looker $3K–$10K/mo, Tableau $500–$3K/mo) plus development time |
| Custom Metrics | Define a metric once, use it everywhere — dashboards, SQL, and AI always return the same answer | Full flexibility — but every metric must be defined, documented, and maintained by your data team |
| SQL / Export / API Access | Managed BigQuery warehouse with included compute and unlimited storage — any tool that supports BigQuery connects natively | Full SQL access — but you manage the warehouse, pay for compute, and maintain the infrastructure |
| 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 an alternative to assembling a data stack?
If you're reconsidering the MDS approach, you're likely hitting one of these walls: spiraling costs that exceeded projections, the 6–12 month timeline to useful insights, vendor fragmentation and finger-pointing when things break, or the bus factor risk of depending on one engineer.
What to look for instead of assembling a stack
One product, not 6–8 tools. Every additional vendor is another contract, another support channel, another failure point, and another finger to point when things break.
Ecommerce-specific analytics out of the box. Attribution, LTV, cohort analysis, and contribution margin should work from day one — not require months of custom dbt modeling.
Predictable cost, not 189% budget overruns. Your analytics budget should be forecastable from month one, not a number that grows 60% beyond projections in Year 1 and reaches $2.3M by Year 3.
A warehouse you own with no assembly required. Full SQL access, any BI tool connects, and you keep everything if you leave. Ask any vendor: if we leave, what happens to our data, dashboards, and team's work?
How SourceMedium addresses these needs
SourceMedium replaces the entire assembled data stack — warehouse, ETL, transformation, BI, attribution, and AI — with one product on a managed BigQuery warehouse with included compute. 2,500+ automated quality checks run daily, every Looker Studio template is open-source and forkable, and 20 pre-built analytics modules work from day one. No assembly required.
See what ecommerce analytics looks like without assembling a data stack. Request a demo →
More alternatives
Explore other ecommerce analytics platform comparisons.
Ready to stop debating the numbers?
Get started
Tell us a bit about your brand and stack—we’ll follow up shortly.
You're all set