| Client/Server authentication | **Stable** | Clients can connect using MD5 authentication, supported by `libpq` and all Postgres client drivers. PgCat can connect to Postgres using MD5 and SCRAM-SHA-256. |
| Live configuration reloading | **Stable** | Identical to PgBouncer; all settings can be reloaded dynamically (except `host` and `port`). |
| Auth passthrough | **Stable** | MD5 password authentication can be configured to use an `auth_query` so no cleartext passwords are needed in the config file.|
See `Dockerfile` for example deployment using Docker. The pooler is configured to spawn 4 workers so 4 CPUs are recommended for optimal performance. That setting can be adjusted to spawn as many (or as little) workers as needed.
A Docker image is available from `docker pull ghcr.io/postgresml/pgcat:latest`. See our [Github packages repository](https://github.com/postgresml/pgcat/pkgs/container/pgcat).
This will open a terminal in an environment similar to that used in tests. In there, you can compile the pooler, run tests, do some debugging with the test environment, etc. Objects compiled inside the container (and bundled gems) will be placed in `dev/cache` so they don't interfere with what you have on your machine.
In session mode, a client talks to one server for the duration of the connection. Prepared statements, `SET`, and advisory locks are supported. In terms of supported features, there is very little if any difference between session mode and talking directly to the server.
To use session mode, change `pool_mode = "session"`.
In transaction mode, a client talks to one server for the duration of a single transaction; once it's over, the server is returned to the pool. Prepared statements, `SET`, and advisory locks are not supported; alternatives are to use `SET LOCAL` and `pg_advisory_xact_lock` which are scoped to the transaction.
All queries are load balanced against the configured servers using either the random or least open connections algorithms. The most straightforward configuration example would be to put this pooler in front of several replicas and let it load balance all queries.
If the configuration includes a primary and replicas, the queries can be separated with the built-in query parser. The query parser, implemented with the `sqlparser` crate, will interpret the query and route all `SELECT` queries to a replica, while all other queries including explicit transactions will be routed to the primary.
The query parser will do its best to determine where the query should go, but sometimes that's not possible. In that case, the client can select which server it wants using this custom SQL syntax:
All servers are checked with a `;` (very fast) query before being given to a client. Additionally, the server health is monitored with every client query that it processes. If the server is not reachable, it will be banned and cannot serve any more transactions for the duration of the ban. The queries are routed to the remaining servers. If all servers become banned, the ban list is cleared: this is a safety precaution against false positives. The primary can never be banned.
The ban time can be changed with `ban_time`. The default is 60 seconds.
### Sharding
We use the `PARTITION BY HASH` hashing function, the same as used by Postgres for declarative partitioning. This allows to shard the database using Postgres partitions and place the partitions on different servers (shards). Both read and write queries can be routed to the shards using this pooler.
Issuing queries to the pooler can cause additional latency. To reduce its impact, it's possible to include sharding information inside SQL comments sent via the query. This is reasonably easy to implement with ORMs like [ActiveRecord](https://api.rubyonrails.org/classes/ActiveRecord/QueryMethods.html#method-i-annotate) and [SQLAlchemy](https://docs.sqlalchemy.org/en/20/core/events.html#sql-execution-and-connection-events).
PgCat can use the `sqlparser` crate to parse SQL queries and extract the sharding key. This is configurable with the `automatic_sharding_key` setting. This feature is still experimental, but it's the ideal implementation for sharding, requiring no client modifications.
The stats are very similar to what PgBouncer reports and the names are kept to be comparable. They are accessible by querying the admin database `pgcat`, and `pgbouncer` for compatibility.
We also have a [basic Grafana dashboard](https://github.com/postgresml/pgcat/blob/main/grafana_dashboard.json) based on Prometheus metrics that you can import into Grafana and build on it or use it for monitoring.
The config can be reloaded by sending a `kill -s SIGHUP` to the process or by querying `RELOAD` to the admin database. All settings except the `host` and `port` can be reloaded without restarting the pooler, including sharding and replicas configurations.
Mirroring allows to route queries to multiple databases at the same time. This is useful for prewarning replicas before placing them into the active configuration, or for testing different versions of Postgres with live traffic.
