# Amazon Redshift

> AWS-native data warehouse with provisioned and serverless compute

Amazon Redshift is AWS's managed analytical data warehouse, offering provisioned RA3 clusters with managed storage or a serverless mode that scales compute automatically and bills per second.

Website: https://aws.amazon.com/redshift/

## Use it when

- The organization is committed to AWS; VPC networking, IAM, Glue, and existing S3 data make Redshift the shortest path.
- Zero-ETL from Aurora and RDS, or streaming ingest from Kinesis and MSK straight into a materialized view, removes pipelines you would otherwise build.
- Usage is spiky and you want Serverless RPUs billed per second, or steady and you want provisioned RA3 nodes at a predictable rate.
- The team already speaks PostgreSQL-flavored SQL.

## Think twice when

- Multi-cloud or an exit path matters; Redshift is AWS only and its storage format is proprietary, though it reads S3 and Iceberg in place.
- Concurrency spikes are constant; concurrency scaling adds transient clusters, but engines built for high QPS serving (ClickHouse, Pinot) fit that shape better.
- You want open table formats as the primary store; Databricks SQL and lakehouse stacks keep the data engine-neutral.

## How it runs

Fully managed on AWS in two compute models over the same managed storage: provisioned RA3 clusters (hot data on local SSD, the rest tiered to S3) or Serverless capacity in RPUs. Spectrum queries S3 in place; WLM queues and concurrency scaling manage load. Clients connect over JDBC, ODBC, and the Data API.

## Details

### General

| Attribute | Value |
| --- | --- |
| License | Commercial |
| Deployment | Managed, Serverless |
| Operational complexity | Medium |
| Pricing | Subscription |
| Documentation | https://docs.aws.amazon.com/redshift/ |

### Data Warehouses

| Attribute | Value |
| --- | --- |
| Where it runs | AWS only |
| Compute and storage | MPP: separated storage on RG, RA3 and Serverless; coupled on legacy DC2 |
| Storage format | Proprietary (Redshift Managed Storage); reads S3 and Iceberg in place |
| SQL dialect | PostgreSQL-derived |
| Streaming ingest | Native: Kinesis Data Streams and Amazon MSK |
| Concurrent users | WLM queues plus concurrency scaling, up to 10 transient clusters; RPU scaling on Serverless |
| Acceleration | Automatic table optimization, materialized views with auto-rewrite, result cache |
| Billing unit | RPU-second on Serverless, or node-hour on provisioned; managed storage per GB-month |
| Time travel | None: snapshot and table restore instead |
| Access control | IAM and database RBAC, row- and column-level security, dynamic data masking; Lake Formation on the lake side |

## Capabilities

- [Data Warehouses](https://matca.io/capabilities/data-warehouse)

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Source: https://matca.io/amazon-redshift
Last updated: 2026-08-31T11:40:48.324Z