How to Connect to PostgreSQL Using SSIS

In any organization, the quality of analytics and decision-making is directly influenced by the quality and quantity of the data available. With numerous and diverse data sources, it's essential to have the ability to retrieve, process, and load this data into analytics systems. This process is known as ETL (Extract, Transform, Load).

There are many ETL solutions available, and one of the most widely used is Microsoft’s SQL Server Integration Services (SSIS). SSIS offers easy connections to a variety of data sources, a broad range of transformation capabilities, and support for loading data into different destinations.

Devart SSIS Data Flow Components simplify working with various data sources with SSIS. Specifically, Devart SSIS Data Flow Components for PostgreSQL allow us to connect SSIS to PostgreSQL instantly and configure data flow tasks for building efficient ETL processes. Let's explore how this works.

Create data flow tasks for PostgreSQL

Before we start working with SSIS using Devart SSIS Data Flow Components for PostgreSQL, we need to ensure the following prerequisites are in place:

The first stage is creating the SSIS data flow task as follows:

1. Launch Visual Studio, open the necessary project, and go to the Data Flow tab.

2. In the SSIS Toolbox panel, select Devart PostgreSQL Source and drag and drop it into the Data Flow field.

Select PostgreSQL as data source

Configure the SSIS PostgreSQL connection

To configure the PostgreSQL SSIS connector, double-click the Devart PostgreSQL Source and select Create New Connection Manager.

Start configuring SSIS connection to Postgres

Configure the connection settings on the General tab. The following details are required for the SSIS PostgreSQL connection:

  • Server - the name of the database host to connect to
  • Port - the number of a port to communicate with listener on the server. The default value is 5432
  • User Id - the PostgreSQL login account
  • Password - the password for the PostgreSQL login account
  • Database - the name of the database to connect to
  • Schema - the name of the schema to be used once a connection is opened. You can change it later if you need. By default, it is Public

Provide connection details

Check and verify the connection details by clicking Test Connection.

Verify connection details

If necessary, you can adjust the additional desired options on the Advanced tab.

Advanced connection details

Click OK to proceed with configuring the SSIS PostgreSQL task.

Select PostgreSQL data to retrieve using SSIS

After successfully connecting, double-click Devart PostgreSQL Source to open the Source Editor. You can see the list of available tables to choose from on the left.

There is no need to write the SELECT query manually to import PostgreSQL data. Simply drag and drop the desired table into the Query field.

Source editor

You can see the data to be exported immediately in the Preview Data window:

Preview data to retrieve

Also, you can compose custom queries to retrieve more targeted and precise results of the SSIS data import. The Editor provides advanced functionality for writing and executing SQL queries against the PostgreSQL data source, allowing you to select specific columns and use complex statements with JOINs and variables.

Advanced query in the source editor

Essential SSIS ETL tasks for PostgreSQL integration

Devart SSIS Data Flow Components for PostgreSQL are a powerful solution that helps us perform all standard ETL tasks. Among the many advantages of using this solution, it is worth mentioning the following:

Import/Export with CSV, XML, Excel support

With SSIS, you can import and export data in various file formats, including CSV, XML, and Excel. This functionality allows you to automate the data extraction from flat files or structured documents and to load it further into relational databases or other destinations for smooth transfer across systems.

Aggregate, split, and merge data

You can use SSIS to aggregate and summarize data, split large datasets into smaller chunks for better processing, and merge data from multiple sources into a unified output, maintaining data integrity.

Integration with cloud storage

SSIS supports integration with various cloud storage platforms, allowing you to move and manage data between on-premises systems and cloud-based storage solutions, ensuring flexibility and scalability for cloud-based ETL processes.

Replication, backup, data migration

SSIS can be used to duplicate databases, ensure disaster recovery with regular backups, or migrate data between heterogeneous systems, thus becoming a versatile tool for maintaining data continuity and accurate transitions between systems.

All these tasks prove the SSIS's capacities related to working with PostgreSQL databases, while Devart SSIS Data Flow Components for PostgreSQL allows you to configure the data flow tasks with ease and ensure precise data retrieving for more effective ETL processes.

Conclusion

SSIS offers a range of advantages for professionals working with data. Its intuitive interface simplifies task configuration, while its excellent scalability and security ensure data protection. As a Microsoft product, SSIS integrates seamlessly with other Microsoft solutions, providing strong support and dependability. It is often the ideal choice for ETL tasks, offering a more cost-effective alternative to cloud-based solutions. Additionally, SSIS can be extended with third-party tools, such as Devart SSIS Data Flow Components, to further enhance its capabilities.

You can download and install the SSIS Data Flow Components for PostgreSQL to improve and optimize your ETL processes when working with PostgreSQL databases. Alternatively, you may consider the SSIS Integration Universal Bundle, which offers a comprehensive set of solutions for both databases and cloud platforms in a single package. A fully functional free trial is available for any of these products, so you can test their full capabilities under real-world conditions.

SSIS Data Flow Components

High-performance SSIS components for popular databases and cloud applications