Amazon Web Services (AWS) is the biggest cloud platform in the world, with over 200 features. In this article, we break down 10 AWS services that support at least some SQL syntax, talk about their use cases, and give examples of how to write queries.
| Service | Description | SQL Support | Use Case |
|---|---|---|---|
| RDS | Postgres, MySQL, etc. | Full | Small-medium web apps |
| Aurora | Serverless databases | Full | Serverless apps |
| Redshift | Data warehouse | Full | OLAP, Petabytes of data, analytics |
| DynamoDB | NoSQL database | Some – PartiSQL | Ecommerce, building fast |
| Keyspaces | Managed Cassandra (key value) | Some – CQL | Messaging |
| Neptune | Graph database | Some – openCypher | Social networks |
| Timestream | Time series database | Partial | IOT, Logging |
| Quantum Ledger | Cryptographically verified transactions | Some – PartiSQL | Finance |
| Athena | Ad-hoc queries on S3 | Some – CTAS | Historical data |
| Babelfish | MSFT SQL Server on Aurora | Full | .NET |
The table above shows how SQL support varies between the services. A graph database cannot be queried in the same way as a classic relational database, and various subsets of SQL, like PartiQL, have emerged to fit these models. In fact, even within standard SQL, there are many SQL dialects for different companies like Oracle and Microsoft.
