Best Cloud Data Warehouses Software
What 10 leading AI models recommend
Top Recommendations
#1
Snowflake
Mentioned by
10/10
models
Average rank: 1.2
Gemini FGemini Pclaude-sonnet-4.5+7 more
#2
Google BigQuery
Mentioned by
10/10
models
Average rank: 2.3
Gemini FGemini Pclaude-sonnet-4.5+7 more
#3
Amazon Redshift
Mentioned by
10/10
models
Average rank: 2.5
Gemini FGemini Pclaude-sonnet-4.5+7 more
#4
Microsoft Azure Synapse Analytics
Mentioned by
9/10
models
Average rank: 4.1
Gemini Fclaude-sonnet-4.5claude-opus-4.5+6 more
#5
Databricks SQL
Mentioned by
5/10
models
Average rank: 4.8
claude-sonnet-4.5claude-opus-4.5mistral-large-2512+2 more
#6
BigQuery ML
Mentioned by
5/10
models
Gemini FGemini Pclaude-sonnet-4.5+2 more
What Each AI Model Says
D
DeepSeek V3
- 1Power BI+
- 2Google Cloud AI/ML tools+
?
glm-4.7
- 5Databricks SQL+
?
mistral-large-2512
- 5Databricks SQL+
- 6Oracle Autonomous Data Warehouse~
?
gpt-5.1
- 4Microsoft Azure Synapse Analytics+
- 4Microsoft Fabric+
- 5Databricks Lakehouse+
- 6Oracle Autonomous Data Warehouse (ADW)+
?
gpt-4o-mini
- 4Microsoft Azure Synapse Analytics+
- 5IBM Db2 Warehouse on Cloud+
?
claude-sonnet-4.5
- 2Google BigQuery+
- 3Amazon Redshift+
- 4Databricks SQL+
- 5Microsoft Azure Synapse Analytics+
- 6Oracle Autonomous Data Warehouse+
G
Gemini 2.5 Flash
- 1Teradata VantageCloud+
- 2Vertica+
- 3ClickHouse Cloud+
- 4Delta Lake+
?
llama-3.3-70b-instruct:free
- 1Amazon Redshift+
- 2Google BigQuery+
- 3Snowflake+
- 4Microsoft Azure Synapse Analytics+
- 5IBM Cloud Data Warehouse~
G
Gemini 2.5 Pro
- 1Vertex AI+
- 2BigQuery ML+
- 3Snowpark~
?
claude-opus-4.5
- 2Amazon Redshift+
- 3Google BigQuery+
- 4Microsoft Azure Synapse Analytics+
- 5Databricks SQL+
- 6Oracle Autonomous Data Warehouse+
Complete Rankings
| Rank | Product/Company | Models Mentioning | Avg. Rank | Mentioned By |
|---|---|---|---|---|
| 1 | Snowflake | 10/10 | 1.2 | Gemini FGemini Pclaude-sonnet-4.5claude-opus-4.5gpt-4o-minigpt-5.1llama-3.3-70b-instruct:freemistral-large-2512DeepSeekglm-4.7 |
| 2 | Google BigQuery | 10/10 | 2.3 | Gemini FGemini Pclaude-sonnet-4.5claude-opus-4.5gpt-4o-minigpt-5.1llama-3.3-70b-instruct:freemistral-large-2512DeepSeekglm-4.7 |
| 3 | Amazon Redshift | 10/10 | 2.5 | Gemini FGemini Pclaude-sonnet-4.5claude-opus-4.5gpt-4o-minigpt-5.1llama-3.3-70b-instruct:freemistral-large-2512DeepSeekglm-4.7 |
| 4 | Microsoft Azure Synapse Analytics | 9/10 | 4.1 | Gemini Fclaude-sonnet-4.5claude-opus-4.5gpt-4o-minigpt-5.1llama-3.3-70b-instruct:freemistral-large-2512DeepSeekglm-4.7 |
| 5 | Databricks SQL | 5/10 | 4.8 | claude-sonnet-4.5claude-opus-4.5mistral-large-2512DeepSeekglm-4.7 |
| 6 | BigQuery ML | 5/10 | - | Gemini FGemini Pclaude-sonnet-4.5claude-opus-4.5glm-4.7 |
| 7 | Serverless Architecture | 4/10 | 3.0 | Gemini FGemini Pclaude-opus-4.5gpt-4o-mini |
| 8 | Redshift Spectrum | 4/10 | 3.0 | Gemini Fmistral-large-2512DeepSeekglm-4.7 |
| 9 | Complexity | 4/10 | 4.0 | claude-sonnet-4.5claude-opus-4.5mistral-large-2512glm-4.7 |
| 10 | Oracle Autonomous Data Warehouse | 4/10 | 6.0 | claude-sonnet-4.5claude-opus-4.5llama-3.3-70b-instruct:freemistral-large-2512 |
| 11 | Real-Time Analytics | 3/10 | 3.0 | Gemini Pgpt-4o-miniglm-4.7 |
| 12 | Lakehouse Architecture | 3/10 | - | Gemini Fclaude-opus-4.5glm-4.7 |
| 13 | Cost Management | 2/10 | 1.0 | Gemini Pgpt-4o-mini |
| 14 | Vendor lock-in | 2/10 | 2.0 | mistral-large-2512DeepSeek |
| 15 | Deep AWS integration | 2/10 | 3.0 | gpt-5.1mistral-large-2512 |
| 16 | Databricks | 2/10 | 4.5 | Gemini FGemini P |
| 17 | Lakehouse architecture | 2/10 | 5.0 | mistral-large-2512DeepSeek |
| 18 | Redshift Serverless | 2/10 | - | claude-sonnet-4.5claude-opus-4.5 |
| 19 | Separation of Compute and Storage | 2/10 | - | Gemini FGemini P |
| 20 | Delta Lake | 2/10 | - | Gemini Fclaude-sonnet-4.5 |
| 21 | Multi-cloud support | 2/10 | - | claude-sonnet-4.5DeepSeek |
| 22 | Cost | 2/10 | - | claude-sonnet-4.5glm-4.7 |
| 23 | Power BI | 2/10 | - | claude-sonnet-4.5DeepSeek |
| 24 | Unified Platform | 2/10 | - | claude-opus-4.5glm-4.7 |
| 25 | Separation of Storage and Compute | 1/10 | 1.0 | gpt-4o-mini |
| 26 | Cost unpredictability | 1/10 | 1.0 | mistral-large-2512 |
| 27 | Separation of storage & compute | 1/10 | 1.0 | mistral-large-2512 |
| 28 | Multi-cloud & cloud-agnostic | 1/10 | 1.0 | mistral-large-2512 |
| 29 | Cost predictability | 1/10 | 1.0 | gpt-5.1 |
| 30 | Strong for semi-structured data | 1/10 | 1.0 | gpt-5.1 |
| 31 | Separation of storage and compute | 1/10 | 1.0 | gpt-5.1 |
| 32 | True cloud-native, multi-cloud | 1/10 | 1.0 | gpt-5.1 |
| 33 | Multi-Cloud Support | 1/10 | 1.0 | gpt-4o-mini |
| 34 | Excellent for very large datasets & log/event analytics | 1/10 | 2.0 | gpt-5.1 |
| 35 | Fully serverless | 1/10 | 2.0 | gpt-5.1 |
| 36 | Concurrency Limitations | 1/10 | 2.0 | gpt-4o-mini |
| 37 | Performance | 1/10 | 2.0 | gpt-4o-mini |
| 38 | Integration with AWS Ecosystem | 1/10 | 2.0 | gpt-4o-mini |
| 39 | Built-in ML/AI | 1/10 | 2.0 | mistral-large-2512 |
| 40 | Serverless & fully managed | 1/10 | 2.0 | mistral-large-2512 |
| 41 | Cost unpredictability (on-demand) | 1/10 | 2.0 | gpt-5.1 |
| 42 | Integrated with Google Cloud & AI | 1/10 | 2.0 | gpt-5.1 |
| 43 | Complex tuning | 1/10 | 3.0 | mistral-large-2512 |
| 44 | More operational tuning vs serverless rivals | 1/10 | 3.0 | gpt-5.1 |
| 45 | Flexible deployment | 1/10 | 3.0 | gpt-5.1 |
| 46 | Cost Structure | 1/10 | 3.0 | gpt-4o-mini |
| 47 | Integrated Analytics Service | 1/10 | 4.0 | gpt-4o-mini |
| 48 | Strong Integration with Microsoft Products | 1/10 | 4.0 | gpt-4o-mini |
| 49 | Microsoft Fabric | 1/10 | 4.0 | gpt-5.1 |
| 50 | Tight integration with Microsoft stack | 1/10 | 4.0 | gpt-5.1 |
| 51 | Unified analytics vision | 1/10 | 4.0 | gpt-5.1 |
| 52 | Platform complexity & overlap | 1/10 | 4.0 | gpt-5.1 |
| 53 | Unified analytics platform | 1/10 | 4.0 | mistral-large-2512 |
| 54 | More complex for “just BI” | 1/10 | 5.0 | gpt-5.1 |
| 55 | IBM Cloud Data Warehouse | 1/10 | 5.0 | llama-3.3-70b-instruct:free |
| 56 | Not a pure data warehouse | 1/10 | 5.0 | mistral-large-2512 |
| 57 | Strong Analytical Capabilities | 1/10 | 5.0 | gpt-4o-mini |
| 58 | Hybrid Cloud Support | 1/10 | 5.0 | gpt-4o-mini |
| 59 | Complex Pricing Model | 1/10 | 5.0 | gpt-4o-mini |
| 60 | Databricks Lakehouse | 1/10 | 5.0 | gpt-5.1 |
| 61 | Unified data + AI platform | 1/10 | 5.0 | gpt-5.1 |
| 62 | Open table formats & ecosystem | 1/10 | 5.0 | gpt-5.1 |
| 63 | Azure Synapse Analytics | 1/10 | 5.0 | Gemini P |
| 64 | IBM Db2 Warehouse on Cloud | 1/10 | 5.0 | gpt-4o-mini |
| 65 | Oracle Autonomous Data Warehouse (ADW) | 1/10 | 6.0 | gpt-5.1 |
| 66 | “Autonomous” operations | 1/10 | 6.0 | gpt-5.1 |
| 67 | Tight with Oracle ecosystem | 1/10 | 6.0 | gpt-5.1 |
| 68 | Firebolt | 1/10 | 6.0 | DeepSeek |
| 69 | Fully autonomous | 1/10 | 6.0 | mistral-large-2512 |
| 70 | Teradata Cloud | 1/10 | 7.0 | llama-3.3-70b-instruct:free |
| 71 | ClickHouse Cloud | 1/10 | - | Gemini F |
| 72 | Unified Data and AI Platform | 1/10 | - | Gemini F |
| 73 | Flexible Compute Options | 1/10 | - | Gemini F |
| 74 | Unified Analytics Platform | 1/10 | - | Gemini F |
| 75 | Deep AWS Integration | 1/10 | - | Gemini F |
| 76 | Multi-Cloud and Cross-Cloud | 1/10 | - | Gemini F |
| 77 | Near-Zero Administration | 1/10 | - | Gemini F |
| 78 | Data Sharing | 1/10 | - | glm-4.7 |
| 79 | AWS Integration | 1/10 | - | glm-4.7 |
| 80 | Management Overhead | 1/10 | - | glm-4.7 |
| 81 | True Serverless | 1/10 | - | glm-4.7 |
| 82 | Pricing Model | 1/10 | - | glm-4.7 |
| 83 | Power BI Integration | 1/10 | - | glm-4.7 |
| 84 | Scalability | 1/10 | - | llama-3.3-70b-instruct:free |
| 85 | Cost-effectiveness | 1/10 | - | llama-3.3-70b-instruct:free |
| 86 | Ease of use | 1/10 | - | llama-3.3-70b-instruct:free |
| 87 | Real-time data ingestion | 1/10 | - | llama-3.3-70b-instruct:free |
| 88 | AWS ecosystem integration | 1/10 | - | llama-3.3-70b-instruct:free |
| 89 | GCP ecosystem integration | 1/10 | - | llama-3.3-70b-instruct:free |
| 90 | Azure ecosystem integration | 1/10 | - | llama-3.3-70b-instruct:free |
| 91 | Steep learning curve | 1/10 | - | llama-3.3-70b-instruct:free |
| 92 | Separation of compute & storage | 1/10 | - | DeepSeek |
| 93 | Higher cost | 1/10 | - | DeepSeek |
| 94 | Serverless architecture | 1/10 | - | DeepSeek |
| 95 | Google Cloud AI/ML tools | 1/10 | - | DeepSeek |
| 96 | More manual tuning required | 1/10 | - | DeepSeek |
| 97 | Unified analytics | 1/10 | - | DeepSeek |
| 98 | Higher learning curve | 1/10 | - | DeepSeek |
| 99 | Smaller ecosystem | 1/10 | - | DeepSeek |
| 100 | Multi-cluster shared data architecture | 1/10 | - | glm-4.7 |
| 101 | Multi-Cloud | 1/10 | - | glm-4.7 |
| 102 | Architecture Innovation | 1/10 | - | claude-opus-4.5 |
| 103 | Cross-Cloud Portability | 1/10 | - | claude-opus-4.5 |
| 104 | Cost Predictability | 1/10 | - | claude-opus-4.5 |
| 105 | AWS Ecosystem Integration | 1/10 | - | claude-opus-4.5 |
| 106 | Cost Control Challenges | 1/10 | - | claude-opus-4.5 |
| 107 | ML/AI Integration | 1/10 | - | claude-opus-4.5 |
| 108 | Microsoft Ecosystem | 1/10 | - | claude-opus-4.5 |
| 109 | Self-Managing | 1/10 | - | claude-opus-4.5 |
| 110 | Oracle compatibility | 1/10 | - | claude-sonnet-4.5 |
| 111 | Azure-only | 1/10 | - | claude-sonnet-4.5 |
| 112 | Management overhead | 1/10 | - | claude-sonnet-4.5 |
| 113 | GCP lock-in | 1/10 | - | claude-sonnet-4.5 |
| 114 | Zero management | 1/10 | - | claude-sonnet-4.5 |
| 115 | Pricing Complexity | 1/10 | - | Gemini P |
| 116 | Vendor Lock-in | 1/10 | - | Gemini P |
| 117 | Vertex AI | 1/10 | - | Gemini P |
| 118 | Blazing Performance for Ad-Hoc Queries | 1/10 | - | Gemini P |
| 119 | Snowpark | 1/10 | - | Gemini P |
| 120 | Secure Data Sharing | 1/10 | - | Gemini P |
| 121 | Ease of Use & Management | 1/10 | - | Gemini P |
| 122 | Multi-Cloud & Cloud-Agnostic | 1/10 | - | Gemini P |
| 123 | Teradata VantageCloud | 1/10 | - | Gemini F |
| 124 | Vertica | 1/10 | - | Gemini F |
Query Posed to AI Models
"Scalable, cloud-native platforms designed for storing and analyzing large volumes of structured and semi-structured data for business intelligence. Rank the leading vendors in the Cloud Data Warehouses market. For each vendor, explain their key strengths and weaknesses, and which types of businesses they are best suited for."
Generated: January 2, 2026 at 05:26 AM