Databricks vs Materialize
Which one do AI engines recommend, and how do they differ on price, fit and features?
The short answer
Databricks is the stronger AI pick in Data Warehouse: it has a visibility score of 37.9 versus 0 for Materialize.
Choose Databricks if…
- You want the brand AI engines rank higher (37.9 vs 0)
- You need ISO 27001 or ISO 27017 or ISO 27018 or ISO 27701 or SOC 1 or SOC 3 coverage
- You prefer a larger, established vendor (5,000+ employees)
- Lakehouse architecture combining data warehousing with data lake flexibility
Choose Materialize if…
No clear advantage in the published data.
AI visibility side by side
Latest weekly run · Nov 3
| Metric | Databricks | Materialize |
|---|---|---|
| Visibility score | 37.9% | 0% |
| Change vs last week | New | New |
| Rank in Data Warehouse | #4 | #35 |
| Share of voice | 9.3% | 0% |
| Mentions this run | 52 | 0 |
| Positive in AI answers | 35% | — |
The stronger value in each row is marked with a ✓.
Visibility score trend
Weekly runs over the last 60 days
Databricks 0pp · Materialize 0pp over 0 weekly runs.
Engine by engine
Databricks leads on 3 of 3 engines
Head to head in AI answers
0 engine answers name both brands
Features, pricing & fit
| Dimension | Databricks | Materialize |
|---|---|---|
| Pricing model | — | Usage-based |
| Entry price | — | Free; paid from $1.5 / mo |
| Free plan | — | Yes |
| Deployment | Available across all major cloud providers | Fully managed SaaS (Materialize Cloud) or self-managed on your own infrastructure, including air-gapped on-prem |
| Compliance | ISO 27001, ISO 27017, ISO 27018, ISO 27701, SOC 1, SOC 2 Type II, SOC 3 | SOC 2 Type II |
| Support | Technical support on request, Technical documentation | Chatbot and helpdesk tickets (Cloud On-Demand), Dedicated account team and guided onboarding (Cloud Capacity), Community Slack (Community license), Priority support from Materialize (Enterprise license) |
| Founded | 2013 | 2019 |
| Headquarters | San Francisco, CA | New York, NY, United States |
| Employees | 5,000+ | 51–200 |
| Funding | Round at $60B valuation, including secondary sale | Series C · $100M raised |
| Best for | Data engineering, data science, analytics and AI teams at startups and global enterprises | Engineering teams that want to build live data products and fresh context for AI agents and apps using SQL |
Plans side by side
Databricks
Pricing not available.
Materialize
Pros and cons
Themes from the AI answers that mention each brand
Databricks
- Lakehouse architecture combining data warehousing with data lake flexibility
- Strong for machine learning, AI, and data engineering workloads
- Top customer satisfaction ratings alongside Snowflake
- Free trial and free Edition for learning
- Discounts for annual prepaid commitments
- Complex consumption-based pricing with no single fixed price
- Best only when ML, Spark, or Python skills are central to the team
Materialize
Profile in progress.
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
Cite as: SlateIndex, “Databricks vs Materialize”, https://slateindex.ai/compare/databricks-vs-materialize, data of Nov 3, 2026. Licence: CC BY 4.0.