Out of the box readiness: Alternate mechanisms When moving the client applications, the majority of the work goes into replacing the SQL Server drivers with their PostgreSQL equivalents, then migrating the T-SQL code into PL/pgSQL which is complex, time consuming and risky. Three major steps are involved in any migration: moving over the schema, migrating the data, and modifying the client applications. Your goal is to migrate the same app to use a PostgreSQL endpoint and PL/pgSQL. Let’s say you have an application that uses a SQL Server connectivity driver to connect to the database endpoint using the TDS protocol (Tabular Data Stream) and T-SQL (Microsoft’s SQL dialect). Migrating from legacy SQL Server databases can be time-consuming and resource-intensive. Challenges in migrating from a commercial to open-source database In this post, we show how you can migrate from SQL Server to Babelfish for Aurora PostgreSQL. We built Babelfish for Aurora PostgreSQL to make it easier to migrate applications from SQL Server to Amazon Aurora PostgreSQL-Compatible Edition. As a result, organizations struggle to start these types of projects because of the opportunity cost of tying up developers, and the risk of introducing errors when making extensive changes to the application code. However, after the initial database migration is completed, manually rewriting application code, switching out database drivers, and verifying that the application behavior hasn’t changed requires significant effort. You can choose from several different ways to migrate your data and database schema from SQL Server to PostgreSQL. Enterprise customers have repeatedly told us they want to migrate to open-source databases such as PostgreSQL.
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