Preparing the federated server to access data sources through JDBC
JDBC data sources are categorized as Type-1 and Type-2 based on the requirement to download the JDBC driver by the user.
Before you begin
| Data source | Type | Optimized | Quick Start |
|---|---|---|---|
| Amazon Athena | Type 1 | Y | Athena |
| Amazon Redshift | Type 2 | Y | RedShift |
| Apache Derby | Type 1 | Y | Apache Derby |
| Apache Hive | Type 2 | Y | Apache Hive |
| Apache Spark SQL | Type 2 | Y | Apache Spark |
| Autonomous Restful Service | Type 2 | Y | |
| Db2® | Type 2 | Y | Db2 |
| Db2 for z/OS® | Type 2 | Y | Db2 for z/OS |
| DVM server | Type 1 | Y | DVM server |
| Google BigQuery | Type 2 | Y | BigQuery |
| IBM PureData® System for Analytics (formerly Netezza®) | Type 1 | Y | Netezza |
| MariaDB | Type 1 | Y | MariaDB |
| Microsoft SQL server | Type 2 | Y | Microsoft SQL server |
| MySQL CE | |||
| MySQL EE | |||
| Oracle | Type 2 | Y | Oracle |
| Pivotal Greenplum | Type 2 | Y | Greenplum |
| PostgreSQL | Type 2 | Y | PostgreSQL |
| SAP HANA | Type 1 | Y | SAP HANA |
| Salesforce | Type 2 | Y | Salesforce |
| Snowflake | |||
| Teradata | Type 1 | Y | Teradata |
Note: In the Optimized column, "Y" indicates that the JDBC wrapper is optimized to
access these data sources. Data type mapping is optimized to keep the data precise; function mapping
and server attributes are optimized to improve the performance with better SQL pushdown. "N"
indicates that you can also use federation to access these data sources and perform basic
operations, such as querying remote data through JDBC drivers, as long as the required JDBC driver
complies with the JDBC standard. However, because the JDBC wrapper is not optimized, there could be
some data types and functions that are not supported correctly, and performance is not expected to
be as good as performance with optimized data sources.
Files that are stored in Amazon S3 are supported in federation by specifying their path with the LOCATION parameter on the CREATE TABLE statement in Amazon Athena, and then accessing these files through the Amazon Athena data source.
Procedure
Prepare the federated server to access data sources according to the type of JDBC data
source.
- If the JDBC data source type is of Type 1, see Preparing the federated server to access data sources through JDBC of type 1.
- If the JDBC data source type is of Type 2, see Preparing the federated server to access data sources through JDBC of type 2.