Data Warehouses

Amazon Redshift vs Databricks

Compare Amazon Redshift and Databricks side-by-side. See feature differences and pricing in the Data Warehouses category.

Amazon Redshift

by Amazon

No reviews yet

Pricing: Pay as you go: Provisioned at $0.543 per node-hour for ra3.large on demand (US East, Ohio); Serverless $0.36 per RPU-hour. Storage billed apart. Trial credit available.

Amazon Redshift is a cloud data warehouse from Amazon Web Services, run as provisioned clusters or Serverless with usage-based pricing, for teams on AWS.

14 /18 features Full profile

Databricks

by Databricks

No reviews yet

Pricing: Pay as you go per DBU; rates vary by cloud, tier and region. SQL warehouses on AWS Premium: Classic $0.22, Pro $0.55, Serverless $0.70 per DBU. 14-day trial; commitments by quote.

Databricks is a data lakehouse platform for SQL warehousing, data engineering, machine learning and AI agents on open table formats, sold pay as you go.

17 /18 features Full profile

Feature Comparison

Data Warehouses features side-by-side

Feature	Amazon Redshift 14/18 features	Databricks 17/18 features
Independent scaling of storage and compute Compute clusters resized or paused without moving data, and storage billed separately.	Yes	Yes
Serverless query execution Queries run on capacity the service allocates per query, with no cluster to provision.	Yes	Yes
Multi-cluster concurrency scaling Extra compute clusters spin up automatically when query queues form and spin down after.	Yes	Yes
Time travel to prior table states Query or restore a table as it was at any point within a retention window of days.	No	Yes
Zero-copy cloning of databases A full copy of a database or table created instantly by sharing the underlying storage.	No	Yes
Auto-refreshing materialized views Materialized views kept current by the service, incrementally where possible.	Yes	Yes
Native semi-structured columns JSON, Avro or Parquet loaded into a variant-style column and queried by path.	Yes	Yes
External tables on data lake files Files in object storage queried in place as tables in open formats.	Yes	Yes
Open table format interoperability Warehouse tables stored in an open format such as Iceberg that outside engines can read.	Yes	Yes
Streaming row ingestion into tables Rows inserted continuously from streams or landing files, without scheduled batch loads.	Yes	Yes
Live data sharing across accounts Tables shared with another account or organization as live reads, without copying data.	Yes	Yes
Column masking policies Sensitive columns masked dynamically per role at query time.	Yes	Yes
Row access policies Row-level filters applied per role or user by the warehouse itself.	Yes	Yes
Automatic query result reuse Repeated identical queries served from a result cache without recomputation.	Yes	Yes
Workload management queues Queries assigned to resource groups with priorities, memory limits and concurrency caps.	Yes	No
Compute spend limits and alerts Budgets or resource monitors that alert on, or suspend, compute past a spend threshold.	Yes	Yes
Cross-region warehouse replication Databases replicated to another region or cloud with failover for disaster recovery.	No	Yes
In-warehouse Python execution Python code runs inside the warehouse as functions or procedures next to the data.	No	Yes
Overall Rating	No reviews yet	No reviews yet

Amazon Redshift 14/18 features

Independent scaling of storage and compute: Yes
Serverless query execution: Yes
Multi-cluster concurrency scaling: Yes
Time travel to prior table states: No
Zero-copy cloning of databases: No
Auto-refreshing materialized views: Yes
Native semi-structured columns: Yes
External tables on data lake files: Yes
Open table format interoperability: Yes
Streaming row ingestion into tables: Yes
Live data sharing across accounts: Yes
Column masking policies: Yes
Row access policies: Yes
Automatic query result reuse: Yes
Workload management queues: Yes
Compute spend limits and alerts: Yes
Cross-region warehouse replication: No
In-warehouse Python execution: No

No reviews yet

Databricks 17/18 features

Independent scaling of storage and compute: Yes
Serverless query execution: Yes
Multi-cluster concurrency scaling: Yes
Time travel to prior table states: Yes
Zero-copy cloning of databases: Yes
Auto-refreshing materialized views: Yes
Native semi-structured columns: Yes
External tables on data lake files: Yes
Open table format interoperability: Yes
Streaming row ingestion into tables: Yes
Live data sharing across accounts: Yes
Column masking policies: Yes
Row access policies: Yes
Automatic query result reuse: Yes
Workload management queues: No
Compute spend limits and alerts: Yes
Cross-region warehouse replication: Yes
In-warehouse Python execution: Yes

No reviews yet

Pricing

Amazon Redshift

Pay as you go: Provisioned at $0.543 per node-hour for ra3.large on demand (US East, Ohio); Serverless $0.36 per RPU-hour. Storage billed apart. Trial credit available.

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Databricks

Pay as you go per DBU; rates vary by cloud, tier and region. SQL warehouses on AWS Premium: Classic $0.22, Pro $0.55, Serverless $0.70 per DBU. 14-day trial; commitments by quote.

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