Azure Synapse AnalyticsvsDatabricks
How 10 AI models weigh Azure Synapse Analytics against Databricks on the 1 buying question where both came up.
- Azure Synapse Analytics
- 70%of answers named it
- Databricks
- 100%of answers named it
- Placed higher
- 7–33times Azure Synapse Analytics vs Databricks, over 40 model rankings that listed either
- Models leaning
- 2–8toward Azure Synapse Analytics vs Databricks
Which models prefer which
Share of each model's answers that named each product, and how often its ranking put one above the other (a product listed beats one left off) · On the 1 shared question, every wording
| Model | Azure Synapse Analytics | Databricks | Placed higher | Leans |
|---|---|---|---|---|
| Claude Haiku 5.5 | 58% | 100% | 0–4 | Databricks |
| GPT-6 Luna | 17% | 100% | 0–4 | Databricks |
| Gemini 4 Argon | 8% | 100% | 0–4 | Databricks |
| Qwen 3.8 Flash | 100% | 100% | 0–4 | Databricks |
| DeepSeek V4 Pro | 100% | 100% | 3–1 | Azure Synapse Analytics |
| GLM-5.3 | 83% | 100% | 0–4 | Databricks |
| Kimi K3 | 42% | 100% | 0–4 | Databricks |
| MiniMax M3 | 92% | 100% | 0–4 | Databricks |
| Mistral Large 4 | 100% | 100% | 1–3 | Databricks |
| Nemotron 3 Ultra | 100% | 100% | 3–1 | Azure Synapse Analytics |
What the models say about Azure Synapse Analytics
One reason per model, from the shared questions
- Claude Haiku 5.5
Capable Azure warehouse, though Microsoft is steering new work toward Fabric.
- Qwen 3.8 Flash
Solid Azure DW option, though being absorbed by Fabric.
- DeepSeek V4 Pro
Tight Power BI and Azure ecosystem coupling, serverless and provisioned modes.
- GLM-5.3
Azure's dedicated warehouse; capable but being eclipsed by Fabric.
- Kimi K3
Solid enterprise-grade option for Azure shops, though Fabric supersedes it
- MiniMax M3
Tight Azure integration, hybrid serverless + dedicated pools.
- Mistral Large 4
Seamless Microsoft stack integration with flexible dedicated and serverless options.
- Nemotron 3 Ultra
Deep Azure integration, serverless + dedicated
What the models say about Databricks
One reason per model, from the shared questions
- Claude Haiku 5.5
Lakehouse architecture excels at mixed analytics, ML, and large-scale data engineering.
- GPT-6 Luna
Strong lakehouse analytics with excellent support for open formats and machine learning workflows.
- Gemini 4 Argon
Combines warehouse performance with lakehouse economics, making it unbeatable for AI-driven organizations.
- Qwen 3.8 Flash
Dominant lakehouse; strong SQL warehouse plus AI workloads.
- DeepSeek V4 Pro
Lakehouse architecture unifies warehouse and ML workloads on open formats.
- GLM-5.3
Lakehouse leader excelling at large-scale, ML, and streaming workloads.
- Kimi K3
Best lakehouse unification of warehousing and AI/ML on open formats.
- MiniMax M3
Best for unified data + AI workloads, Delta Lake, strong performance.
- Mistral Large 4
Unified lakehouse architecture excels for data engineering and ML workloads.
- Nemotron 3 Ultra
Lakehouse convergence, Photon engine, Unity Catalog
Tracked since October 25, 2026. Each time the panel answers these questions again, both shares are added here.
Question by question
Share of all answers that named each, every wording pooled, with its place among every product named · Both-named questions first
| Question | Azure Synapse Analytics | Databricks |
|---|---|---|
| Best cloud data warehouses | 70% #8 | 100% #1 |