Data Warehouses

Amazon Redshift vs Azure Synapse Analytics

Compare Amazon Redshift and Azure Synapse Analytics 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

Azure Synapse Analytics

by Microsoft

No reviews yet

Pricing: Pay as you go in USD: dedicated SQL pool from $876 a month (less on 1- or 3-year reservations), serverless SQL $5 per TB processed, Spark pools $0.143 per vCore-hour

Azure Synapse Analytics is Microsoft's cloud data warehouse and analytics service, joining T-SQL pools, Spark and pipelines on Azure with pay-as-you-go billing.

12 /18 features Full profile

Feature Comparison

Data Warehouses features side-by-side

Feature	Amazon Redshift 14/18 features	Azure Synapse Analytics 12/18 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	No
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	No
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	No
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	No
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	Yes
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	No
In-warehouse Python execution Python code runs inside the warehouse as functions or procedures next to the data.	No	No
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

Azure Synapse Analytics 12/18 features

Independent scaling of storage and compute: Yes
Serverless query execution: Yes
Multi-cluster concurrency scaling: No
Time travel to prior table states: Yes
Zero-copy cloning of databases: No
Auto-refreshing materialized views: Yes
Native semi-structured columns: No
External tables on data lake files: Yes
Open table format interoperability: Yes
Streaming row ingestion into tables: Yes
Live data sharing across accounts: No
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

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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Azure Synapse Analytics

Pay as you go in USD: dedicated SQL pool from $876 a month (less on 1- or 3-year reservations), serverless SQL $5 per TB processed, Spark pools $0.143 per vCore-hour

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