Prompt
Which lakehouse database services are known for separating storage and compute to control costs at scale?
Latest observation
Lakehouse database services that are well known for separating storage and compute—which helps control costs at scale—include:
-
Databricks Lakehouse / Databricks SQL
Uses cloud object storage for data and separate compute clusters/warehouses. -
Snowflake
A classic example of independent storage and compute, with separate virtual warehouses. -
Google BigQuery
Serverless architecture with storage and compute decoupled. -
Amazon Redshift Serverless / Redshift Spectrum
Redshift supports more separation through serverless and external storage patterns. -
Azure Synapse Analytics
Especially in serverless SQL and Spark-based setups, storage and compute are separated. -
Apache Iceberg-based platforms
Many lakehouse services built on Iceberg (such as Starburst, Dremio, Trino-based platforms) separate storage and compute by design. -
Delta Lake-based platforms
Similar pattern across platforms using Delta Lake on object storage with independent compute.
If you want, I can also give you:
- a vendor comparison table,
- the cheapest options for small teams, or
- the best choices for AWS / Azure / GCP.
Observation history
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Meta AI,
Qwen.
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