Snowflake virtual warehouses
E434095
Snowflake virtual warehouses are scalable compute clusters in the Snowflake cloud data platform that execute queries and data processing workloads independently of storage.
All labels observed (4)
| Label | Occurrences |
|---|---|
| Snowflake virtual warehouses canonical | 2 |
| Snowflake warehouse | 2 |
| Snowflake SQL engine | 1 |
| Snowflake warehouses | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T4326294 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snowflake virtual warehouses Context triple: [Python (via Snowpark), compatibleWith, Snowflake virtual warehouses]
-
A.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
B.
Snowflake Native Apps
Snowflake Native Apps are applications built and deployed directly within the Snowflake Data Cloud, allowing developers to create, distribute, and monetize data-intensive solutions that run securely where the data lives.
-
C.
Scala (via Snowpark)
Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
-
D.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
E.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Snowflake virtual warehouses Target entity description: Snowflake virtual warehouses are scalable compute clusters in the Snowflake cloud data platform that execute queries and data processing workloads independently of storage.
-
A.
Snowflake Data Cloud
Snowflake Data Cloud is a cloud-native data platform that enables organizations to store, integrate, and analyze data at scale across multiple clouds with a unified, fully managed service.
-
B.
Snowflake Native Apps
Snowflake Native Apps are applications built and deployed directly within the Snowflake Data Cloud, allowing developers to create, distribute, and monetize data-intensive solutions that run securely where the data lives.
-
C.
Scala (via Snowpark)
Scala (via Snowpark) is a way to use the Scala programming language within Snowflake’s Snowpark developer framework to build and run data pipelines, transformations, and applications directly in the Snowflake Data Cloud.
-
D.
Databricks
Databricks is a cloud-based data and AI company best known for its unified analytics platform built around Apache Spark, enabling large-scale data engineering, data science, and machine learning workloads.
-
E.
Azure Synapse Analytics
Azure Synapse Analytics is a cloud-based analytics service from Microsoft that unifies big data and data warehousing to enable large-scale data integration, exploration, and business intelligence.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
Snowflake feature
ⓘ
compute cluster ⓘ |
| accesses |
Snowflake databases
ⓘ
Snowflake schemas ⓘ Snowflake tables ⓘ |
| configuredBy |
auto-resume setting
ⓘ
auto-suspend timeout ⓘ maximum cluster count ⓘ minimum cluster count ⓘ resource monitor ⓘ warehouse size ⓘ |
| createdWith | CREATE WAREHOUSE command ⓘ |
| deletedWith | DROP WAREHOUSE command ⓘ |
| hasGranularity | per-warehouse credit usage ⓘ |
| hasProperty |
can be started and stopped on demand
ⓘ
do not store data persistently ⓘ isolation between workloads ⓘ pay-per-second billing ⓘ scale out by adding clusters ⓘ scale up by changing size ⓘ |
| hasRole |
execute queries
ⓘ
perform data processing workloads ⓘ |
| managedBy | Snowflake account administrators ⓘ |
| modifiedWith | ALTER WAREHOUSE command ⓘ |
| monitoredWith |
ACCOUNT_USAGE views
ⓘ
INFORMATION_SCHEMA views ⓘ |
| partOf |
Snowflake cloud data platform
ⓘ
linked to:
Snowflake Data Cloud
|
| runsOn |
Amazon Web Services
ⓘ
Google Cloud Platform ⓘ
linked to:
Google Cloud
Microsoft Azure ⓘ
linked to:
Azure
cloud infrastructure ⓘ |
| separateFrom | Snowflake storage layer ⓘ |
| supportsFeature |
query result caching usage
ⓘ
warehouse-level resource governance ⓘ workload isolation by separate warehouses ⓘ |
| supportsProperty |
automatic resume
ⓘ
automatic suspension ⓘ concurrency scaling ⓘ elastic scalability ⓘ independent scaling of compute ⓘ multi-cluster configuration ⓘ |
| usedFor |
BI and reporting workloads
ⓘ
ETL and ELT pipelines ⓘ batch processing ⓘ data loading ⓘ data science workloads ⓘ data transformation ⓘ interactive analytics ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Snowflake virtual warehouses Description of subject: Snowflake virtual warehouses are scalable compute clusters in the Snowflake cloud data platform that execute queries and data processing workloads independently of storage.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Snowflake virtual warehouses
linked to: Snowflake virtual warehouses
linked to: Snowflake virtual warehouses
linked to: Snowflake virtual warehouses