I’m happy to announce release 0.8 of pg_statviz, the minimalist extension and utility pair for time series analysis and visualization of PostgreSQL internal statistics.

This release adds support for PostgreSQL 18, adapting to significant catalog view changes introduced in this release:

• I/O statistics now include byte-based metrics: The pg_stat_io view now reports I/O activity in bytes (read_bytes, write_bytes, extend_bytes) rather than just operation counts, providing more granular insight into system I/O patterns.
• WAL statistics reorganization: PostgreSQL 18 moves WAL write and sync statistics from pg_stat_wal to pg_stat_io (where object = 'wal'), consolidating I/O metrics across different subsystems.

The extension automatically detects your PostgreSQL version and uses the appropriate catalog views, maintaining backward compatibility with PostgreSQL 14 through 17 while taking advantage of the enhanced metrics available in PostgreSQL 18. The Python utility has also been updated to handle both the new byte-based I/O metrics and the operation counts from earlier versions.

This release also bumps the minimum Python requirement to 3.11+ and updates the numpy dependency to 2.3.4.

pg_statviz takes the view that everything should be light and minimal. Unlike commercial monitoring platforms, it doesn’t require invasive agents or open connections to the database — it all lives inside your database. The extension is plain SQL and pl/pgSQL and doesn’t require modules to be loaded, the visualization utility is separate and can be run from anywhere, and your data is free and easy to export.

• You can download and install pg_statviz from the PostgreSQL repositories or PGXN.
• The utility can also be installed from PyPi.
• Manual installation is also possible.