AWS AmazonRDS documentation change
Summary
Updated terminology from 'destination database' to 'target database', added Amazon SageMaker as a supported destination, clarified data type mappings for analytics warehouses, and added a note about SageMaker lakehouse integration limitations
Security assessment
The changes primarily focus on terminology updates, expanding supported destinations (Redshift/SageMaker), and operational guidance for integration refreshes. There is no mention of vulnerabilities, access controls, encryption, or authentication mechanisms. The note about SageMaker lakehouse integration limitations relates to operational procedures rather than security controls.
Diff
diff --git a/AmazonRDS/latest/AuroraUserGuide/zero-etl.querying.md b/AmazonRDS/latest/AuroraUserGuide/zero-etl.querying.md index 4df7c8ecd..6c3d8c0df 100644 --- a//AmazonRDS/latest/AuroraUserGuide/zero-etl.querying.md +++ b//AmazonRDS/latest/AuroraUserGuide/zero-etl.querying.md @@ -5 +5 @@ -Creating a destination database in Amazon RedshiftAdding data to the source DB clusterQuerying your Aurora data in Amazon RedshiftData type differencesDDL operations for Aurora PostgreSQL +Creating a target databaseAdding data to the source DB clusterQuerying your Aurora data in Amazon RedshiftData type differencesDDL operations for Aurora PostgreSQL @@ -7 +7 @@ Creating a destination database in Amazon RedshiftAdding data to the source DB c -# Adding data to a source Aurora DB cluster and querying it in Amazon Redshift +# Adding data to a source Aurora DB cluster and querying it @@ -9 +9 @@ Creating a destination database in Amazon RedshiftAdding data to the source DB c -To finish creating a zero-ETL integration that replicates data from Amazon Aurora into Amazon Redshift, you must create a destination database in Amazon Redshift. +To finish creating a zero-ETL integration that replicates data from Amazon Aurora into Amazon Redshift, you must create a database in the target destination. @@ -11 +11 @@ To finish creating a zero-ETL integration that replicates data from Amazon Auror -First, connect to your Amazon Redshift cluster or workgroup and create a database with a reference to your integration identifier. Then, you can add data to your source Aurora DB cluster and see it replicated in Amazon Redshift. +For connections with Amazon Redshift, connect to your Amazon Redshift cluster or workgroup and create a database with a reference to your integration identifier. Then, you can add data to your source Aurora DB cluster and see it replicated in Amazon Redshift or Amazon SageMaker. @@ -15 +15 @@ First, connect to your Amazon Redshift cluster or workgroup and create a databas - * Creating a destination database in Amazon Redshift + * Creating a target database @@ -28 +28 @@ First, connect to your Amazon Redshift cluster or workgroup and create a databas -## Creating a destination database in Amazon Redshift +## Creating a target database @@ -30 +30 @@ First, connect to your Amazon Redshift cluster or workgroup and create a databas -Before you can start replicating data into Amazon Redshift, after you create an integration, you must create a destination database in your target data warehouse. This destination database must include a reference to the integration identifier. You can use the Amazon Redshift console or the Query editor v2 to create the database. +Before you can start replicating data into Amazon Redshift, after you create an integration, you must create a database in your target data warehouse. This database must include a reference to the integration identifier. You can use the Amazon Redshift console or the Query editor v2 to create the database. @@ -36 +36 @@ For instructions to create a destination database, see [Create a destination dat -After you configure your integration, you can add some data to the Aurora DB cluster that you want to replicate into your Amazon Redshift data warehouse. +After you configure your integration, you can add some data to the Aurora DB cluster that you want to replicate into your data warehouse. @@ -40 +40 @@ After you configure your integration, you can add some data to the Aurora DB clu -There are differences between data types in Amazon Aurora and Amazon Redshift. For a table of data type mappings, see Data type differences between Aurora and Amazon Redshift databases. +There are differences between data types in Amazon Aurora and the target analytics warehouse. For a table of data type mappings, see Data type differences between Aurora and Amazon Redshift databases. @@ -80 +80 @@ The following example uses the `[psql](https://www.postgresql.org/docs/current/a -After you add data to the Aurora DB cluster, it's replicated into Amazon Redshift and is ready to be queried. +After you add data to the Aurora DB cluster, it's replicated into the destination database and is ready to be queried. @@ -92 +92 @@ After you add data to the Aurora DB cluster, it's replicated into Amazon Redshif - + @@ -116 +116 @@ For case-sensitivity, use double quotes (" ") for schema, table, and column name -The following tables show the mappings of an Aurora MySQL or Aurora PostgreSQL data type to a corresponding Amazon Redshift data type. _Amazon Aurora currently supports only these data types for zero-ETL integrations._ +The following tables show the mappings of an Aurora MySQL or Aurora PostgreSQL data type to a corresponding destination data type. _Amazon Aurora currently supports only these data types for zero-ETL integrations._ @@ -118 +118,5 @@ The following tables show the mappings of an Aurora MySQL or Aurora PostgreSQL d -If a table in your source DB cluster includes an unsupported data type, the table goes out of sync and isn't consumable by the Amazon Redshift target. Streaming from the source to the target continues, but the table with the unsupported data type isn't available. To fix the table and make it available in Amazon Redshift, you must manually revert the breaking change and then refresh the integration by running `[ALTER DATABASE...INTEGRATION REFRESH](https://docs.aws.amazon.com/redshift/latest/dg/r_ALTER_DATABASE.html)`. +If a table in your source DB cluster includes an unsupported data type, the table goes out of sync and isn't consumable by the destination target. Streaming from the source to the target continues, but the table with the unsupported data type isn't available. To fix the table and make it available in the target destination, you must manually revert the breaking change and then refresh the integration by running `[ALTER DATABASE...INTEGRATION REFRESH](https://docs.aws.amazon.com/redshift/latest/dg/r_ALTER_DATABASE.html)`. + +###### Note + +You can't refresh zero-ETL integrations with an Amazon SageMaker lakehouse. Instead, delete and try to create the integration again. @@ -131 +135 @@ If a table in your source DB cluster includes an unsupported data type, the tabl -Aurora MySQL data type | Amazon Redshift data type | Description | Limitations +Aurora MySQL data type | Target data type | Description | Limitations @@ -183 +187 @@ cid | BIGINT | Signed eight-byte integer | None -cidr | VARCHAR(19) | Variable-length string value up to 19 characters | +cidr | VARCHAR(19) | Variable-length string value up to 19 characters | None @@ -299 +303 @@ DDL operation | Redshift system response -`CREATE TABLE` | Amazon Redshift creates the table. Some operations cause table creation to fail, such as creating a table without a primary key or performing declarative partitioning. For more information, see [Aurora PostgreSQL limitations](./zero-etl.html#zero-etl.reqs-lims-apg) and [Troubleshooting Aurora zero-ETL integrations with Amazon Redshift](./zero-etl.troubleshooting.html). +`CREATE TABLE` | Amazon Redshift creates the table. Some operations cause table creation to fail, such as creating a table without a primary key or performing declarative partitioning. For more information, see [Aurora PostgreSQL limitations](./zero-etl.html#zero-etl.reqs-lims-apg) and [Troubleshooting Aurora zero-ETL integrations](./zero-etl.troubleshooting.html).