Ecosystem integration
AnalyticDB for PostgreSQL connects to a broad set of tools across your data stack — from extract, transform, and load (ETL) pipelines and business intelligence (BI) dashboards to data migration services and logging systems. The following tables list supported tool categories and products.
Supported tools
| Category | Tools |
|---|---|
| Data development and management | Data Management (DMS), DataWorks, Dataphin |
| BI and visualization | Quick BI, Tableau, QlikView, FineBI, Smartbi, DataV |
| Stream processing | Flink, DataHub |
| ETL | DataStage, Informatica, Kettle, Automation |
| Data migration | Data Transmission Service (DTS), DataX, OGG, Data Systems Group (DSG) |
| Logging | Logstash, Kafka |
| Big data | Hadoop, MaxCompute, Data Lake |
| Traditional data warehouse | Teradata, Greenplum, DB2 |
| Database | Oracle, MySQL, PostgreSQL |
Client interfaces
AnalyticDB for PostgreSQL supports JDBC, ODBC, and libpq as client interfaces. Any tool or application that connects through these standard interfaces can work with AnalyticDB for PostgreSQL.
Built-in engines
AnalyticDB for PostgreSQL includes two built-in engines for advanced data analysis:
MADlib — an in-database data mining library that runs analytical functions directly inside the database engine
PostGIS — a spatial database extension that adds support for geographic objects and location-based queries
What's next
