Cortex
By Cortex
Cortex is a fully managed, LLM-powered REST service designed for business users who need to convert natural-language questions into SQL queries.
Publisher review
Cortex is a fully managed, LLM-powered REST service designed for business users who need to convert natural-language questions into SQL queries. It integrates directly with Snowflake, leveraging semantic models (YAML) to bridge the gap between business users and databases. Cortex Analyst, a key component, is close to 2x more accurate than single-shot SQL generation using state-of-the-art LLMs like GPT-4o, achieving 90%+ SQL accuracy on real-world use cases.
It runs securely inside Snowflake Cortex, inheriting Snowflake's RBAC, masking, and row access policies, and can be integrated into existing workflows via REST API. Cortex is particularly suited for organizations already using Snowflake and seeking to enhance their analytics capabilities with AI-driven SQL generation. Cortex operates by selecting the best combination of LLMs at runtime, including Mistral Large and Codestral, to generate highly accurate SQL responses.
It uses semantic models or views to ground the SQL generation process, ensuring that the queries are relevant and accurate. The service is designed to be deterministic and reproducible, with governance enforced before SQL execution. However, it is stateless between conversational turns, meaning it cannot reference results from prior queries, and it is limited to SQL-only queries, excluding open-ended analysis.
Cortex's market position is strong within the Snowflake ecosystem, but it faces competition from external AI tools like Basejump AI, which offer multi-warehouse support and deterministic SQL generation. Cortex's integration with Snowflake's security perimeter is a significant advantage, but it also means that it is locked into the Snowflake environment, limiting its flexibility for users with multi-cloud or multi-warehouse setups. The service's semantic model size is capped at 1 MB, which can be restrictive for complex data models, and it does not infer joins, requiring explicit relationships to be defined.
Cortex's pricing is based on token consumption and serving compute, which can lead to unpredictable costs, as evidenced by a documented case where a single query cost $5K due to high token usage. Despite these trade-offs, Cortex remains a powerful tool for organizations looking to leverage Snowflake's infrastructure for AI-driven analytics.
How it works
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Natural language to SQL
Converts natural-language questions into SQL queries using semantic models (YAML) and LLMs like Mistral Large and Codestral.
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Snowflake integration
Runs securely inside Snowflake Cortex, inheriting Snowflake's RBAC, masking, and row access policies.
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Semantic model support
Uses semantic models or views to bridge the gap between business users and databases, ensuring accurate SQL generation.
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REST API integration
Can be integrated into existing business workflows via REST API, enabling seamless adoption.
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Multi-model selection
Selects the best combination of LLMs at runtime to generate highly accurate SQL responses.
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Deterministic SQL
Designed for deterministic, reproducible SQL generation across many warehouses with governance enforced before execution.
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High accuracy
Achieves 90%+ SQL accuracy on real-world use cases, outperforming single-shot SQL generation with GPT-4o.
Strengths and trade-offs
Strengths
- Cortex Analyst is close to 2x more accurate than single-shot SQL generation using GPT-4o, reaching 90%+ SQL accuracy on real-world use cases.
- Cortex inherits Snowflake's RBAC, masking, and row access policies, ensuring robust security and governance.
- Cortex can be integrated into existing business workflows via REST API, simplifying adoption.
- Cortex uses Mistral Large and Codestral LLMs for natural language understanding and SQL generation, ensuring high accuracy.
Trade-offs
- Cortex is stateless between conversational turns, meaning it cannot reference results from prior queries.
- Cortex is limited to SQL-only queries, excluding open-ended analysis like 'what trends do you observe?'.
- Cortex's semantic model size is capped at 1 MB, which can be restrictive for complex data models.
- Cortex's pricing is based on token consumption and serving compute, leading to unpredictable costs.
Pricing context
Pricing is based on token consumption and serving compute, leading to variable costs.
Getting started with Cortex
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Sign up for Cortex
Access Cortex through your Snowflake account. Navigate to Snowflake Cortex services and enable Cortex for your organization. Verify your permissions to use AI services within Snowflake.
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Connect to Snowflake
Link Cortex to your Snowflake data warehouse. Provide necessary credentials and permissions. Ensure your Snowflake instance meets Cortex's requirements for integration.
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Define semantic models
Create YAML files to define semantic models for your data. Structure tables, columns, and relationships explicitly. Keep models under 1 MB to comply with size limits.
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Submit natural language queries
Use the REST API to send natural language questions to Cortex. Receive generated SQL queries in response. Review the SQL for accuracy before execution.
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Monitor token usage
Track your token consumption and compute costs in Snowflake. Set alerts for unexpected usage spikes. Adjust query complexity or frequency to manage expenses.
Frequently Asked Questions
What is Cortex?
Cortex is a managed REST service that converts natural-language questions into SQL queries using semantic models and LLMs like Mistral Large and Codestral. It integrates with Snowflake, offering high accuracy and secure SQL generation for business users.
How does Cortex integrate with Snowflake?
Cortex runs securely inside Snowflake Cortex, inheriting Snowflake’s RBAC, masking, and row access policies. It leverages semantic models to bridge business users and databases, ensuring accurate SQL generation while maintaining robust security and governance.
What are Cortex’s key features?
Cortex features natural language to SQL conversion, Snowflake integration, semantic model support, REST API integration, and multi-model selection. It achieves 90%+ SQL accuracy, outperforming single-shot SQL generation with GPT-4o, and ensures deterministic SQL generation.
How accurate is Cortex?
Cortex Analyst achieves 90%+ SQL accuracy on real-world use cases, nearly doubling the accuracy of single-shot SQL generation with GPT-4o. It selects the best combination of LLMs at runtime, ensuring highly accurate and reproducible SQL responses.
What are Cortex’s limitations?
Cortex is stateless between conversational turns, cannot reference prior queries, and is limited to SQL-only queries. Its semantic model size is capped at 1 MB, and pricing based on token consumption can lead to unpredictable costs.
How does Cortex handle security?
Cortex inherits Snowflake’s RBAC, masking, and row access policies, ensuring robust security and governance. It runs securely inside Snowflake Cortex, leveraging Snowflake’s security perimeter while generating SQL queries from natural language inputs.
Alternatives
How Cortex compares
Direct head-to-head against 2 competitors. Picked by 7wData.
Cortex
- Pricing
- Pricing is based on token consumption and serving compute, leading to variable costs.
- Target
- Cortex is a fully managed, LLM-powered REST service designed for business users who need to convert natural-language questions into SQL queries.
- Strength
- Cortex Analyst is close to 2x more accurate than single-shot SQL generation using GPT-4o, reaching 90%+ SQL accuracy on real-world use cases.
- Watch for
- Cortex is stateless between conversational turns, meaning it cannot reference results from prior queries.
Databricks Lakehouse AI
- Pricing
- Custom/Contact sales
- Target
- Enterprise AI/ML workloads
- Deployment
- Cloud
- Strength
- Unified data and AI platform
- Watch for
- Complex setup for non-Databricks users
Google Cloud Vertex AI
- Pricing
- Pay-as-you-go
- Target
- Enterprise AI/ML workloads
- Deployment
- Cloud
- Strength
- Pre-trained models and AutoML
- Watch for
- Potential vendor lock-in
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Sources
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