"Extensions allow applications to expand the capabilities of database management systems (DBMSs) with custom logic. However, the extensibility environment for some DBMSs is fraught with perils, causing developers to resort to unorthodox methods to achieve their goals. This paper studies and evaluates the design of DBMS extensibility. First, we provide a comprehensive taxonomy of the types of DBMS extensibility. We then examine the extensibility of six DBMSs: PostgreSQL, MySQL, MariaDB, SQLite, Redis, and DuckDB. We present an automated extension analysis toolkit that collects static and dynamic information on how an extension integrates into the DBMS. Our evaluation of over 400 PostgreSQL extensions shows that 16.8% of them are incompatible with at least one other extension and can cause system failures. These results also show the correlation between these failures and factors related to extension complexity and implementation."
"Extensions allow applications to expand the capabilities of database management systems (DBMSs) with custom logic. However, the extensibility environment for some DBMSs is fraught with perils, causing developers to resort to unorthodox methods to achieve their goals. This paper studies and evaluates the design of DBMS extensibility. First, we provide a comprehensive taxonomy of the types of DBMS extensibility. We then examine the extensibility of six DBMSs: PostgreSQL, MySQL, MariaDB, SQLite, Redis, and DuckDB. We present an automated extension analysis toolkit that collects static and dynamic information on how an extension integrates into the DBMS. Our evaluation of over 400 PostgreSQL extensions shows that 16.8% of them are incompatible with at least one other extension and can cause system failures. These results also show the correlation between these failures and factors related to extension complexity and implementation."
Database Extensions Analyzer: https://github.com/cmu-db/ext-analyzer
Talk: https://www.youtube.com/watch?v=U7v0fubktoY