pgAdmin vs pgBadger

Quick verdict

pgAdmin 4 is the PostgreSQL project's administration and development tool, under the PostgreSQL Licence; the current release is 9.18. Alongside object management, the Query Tool and backup dialogs, its Dashboard tab gives, in the documentation's words, an active analysis of system statistics and usage statistics for the selected server or database: graphs of sessions, transactions per second, tuples in and out and block I/O, a panel of sessions, locks and prepared transactions, and the server configuration. Since version 7.8 a System Statistics tab shows CPU, memory and storage through the system_stats extension. See our pgAdmin review.

pgBadger describes itself as a PostgreSQL log analyser built for speed that produces detailed reports from PostgreSQL log files. It is a single Perl script, maintained by Gilles Darold under the PostgreSQL Licence; the latest release on GitHub is 13.2 (December 2025). It never connects to the database: it reads stderr, syslog, csvlog or jsonlog files (and formats such as pgBouncer, Amazon RDS and Google Cloud SQL logs), locally or over SSH, and writes interactive HTML reports or JSON.

Side by side

Key differences

Different questions: "what is happening" versus "what happened"

pgAdmin's dashboard is a live view. It is the right place to answer "why is the application stuck right now": look at the session list, see which sessions are active or idle in transaction, check the locks panel, and cancel the query or terminate the session from the same screen. The documentation describes this as active analysis; it is not a store of history, so a spike that happened at 3 a.m. is gone by morning.

pgBadger answers the opposite question. Because it reads the log, it can tell you which normalised queries took the most total time yesterday, how many temporary files were written, when checkpoints ran, how many connections arrived per hour, and which errors occurred. Its incremental mode (-I) builds daily reports and cumulative weekly summaries, and -j parses in parallel. What it cannot do is show anything that was not logged.

The logging pgBadger needs

pgBadger depends on PostgreSQL logging that is mostly off by default. Its documentation asks for log_min_duration_statement (0 logs every statement; a higher threshold on busy servers), a log_line_prefix that includes a time escape (%t, %m or %n) and a process escape (%p or %c), and several event settings. The settings pgBadger documents, for stderr logging:

# postgresql.conf (PostgreSQL), settings documented by pgBadger
log_min_duration_statement = 0      # or e.g. 250ms on a busy server
log_line_prefix = '%t [%p]: user=%u,db=%d,app=%a,client=%h '
log_checkpoints = on
log_connections = on
log_disconnections = on
log_lock_waits = on
log_temp_files = 0
log_autovacuum_min_duration = 0
log_error_verbosity = default
lc_messages = 'C'                  # or 'en_US.UTF-8'

pgBadger warns not to enable log_min_duration_statement, log_duration and log_statement together, because that produces wrong counter values and much larger logs, and notes that with log_statement = 'all' nothing is logged through log_min_duration_statement. Two PostgreSQL 18 details are worth knowing: log_checkpoints is already on by default, and log_connections is now a list of aspects (receipt, authentication, authorization, setup_durations, all), with on still accepted for backwards compatibility as the first three. Logging every statement costs disk space and I/O, so many teams start with a threshold such as 250 ms and lower it during an investigation.

Where pg_stat_statements fits

pg_stat_statements is the third piece. It is a PostgreSQL module that keeps cumulative planning and execution statistics per normalised statement in shared memory, so it covers every query without logging each one. It must be added to shared_preload_libraries (with compute_query_id on), which needs a restart, and then enabled with CREATE EXTENSION. The PostgreSQL documentation's own example finds the statements with the highest total time:

-- PostgreSQL: top statements by total execution time
SELECT query, calls, total_exec_time, rows,
       100.0 * shared_blks_hit /
         nullif(shared_blks_hit + shared_blks_read, 0) AS hit_percent
FROM   pg_stat_statements
ORDER  BY total_exec_time DESC
LIMIT  5;

In practice the three complement each other: pg_stat_statements tells you which statements cost the most in total since the last reset, pgBadger shows when they ran, with example parameter values and the surrounding lock waits, temporary files and errors, and pgAdmin lets you see and stop what is running now and run EXPLAIN on a suspect query in the Query Tool. pgBadger does not read pg_stat_statements, and the pgAdmin dashboard does not chart it; you query it yourself or use a monitoring product that does. For more on reading plans, see performance tuning and SQL indexes.

Running them

pgAdmin runs as a desktop application or as a web server shared by a team, and needs a login on each PostgreSQL server; PostgreSQL shows other users' query text only to superusers and roles with sufficient privileges, such as members of pg_read_all_stats. From version 9.13, pgAdmin also offers optional AI Reports (security, performance and design) using a configured LLM provider (Anthropic, OpenAI, Ollama or Docker Model Runner); administrators can disable them. These are generated suggestions, not monitoring history.

pgBadger needs only Perl and access to the log files. It is typically run on a schedule (for example from cron) against the log directory or a remote host over SSH, and its HTML output is published somewhere the team can read. On managed services you first need to download or stream the logs; pgBadger documents formats for Amazon RDS and Google Cloud SQL logs.

Pricing and licensing

Both are free open source software under the PostgreSQL Licence, with no paid edition. pgAdmin is free in desktop and server mode. pgBadger is free; its cost is the extra log volume and storage from the logging settings it needs, and somewhere to run the script and host the reports.

Pricing checked on the vendors' official pages on 7 October 2026. Prices change; confirm before buying.

Where each one leads

Limitations

When to choose each

When neither is right

• You need continuous monitoring with history, dashboards and alerts across many servers: see Prometheus vs Datadog and PostgreSQL monitoring tools.
• You want query-level monitoring linked to application traces: see Datadog vs New Relic and Database Monitoring vs APM.
• You want a free PostgreSQL GUI but not pgAdmin: see pgAdmin alternatives and DBeaver vs pgAdmin.

Final recommendation

Frequently asked questions

Sources

• pgAdmin download page (current version)
• pgAdmin 4 documentation: Tabbed browser and Dashboard
• pgAdmin 4 release notes 7.8 (System Statistics)
• pgAdmin 4 documentation: AI Reports
• pgBadger on GitHub (README, licence, configuration)
• pgBadger releases
• pgBadger documentation
• PostgreSQL documentation: Error reporting and logging
• PostgreSQL documentation: pg_stat_statements
• PostgreSQL documentation: The cumulative statistics system

Checked October 2026.

How we research comparisons: our editorial method.