PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II

PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II

Compare PgBouncer vs. Pgpool-II to see which PostgreSQL connection pooler offers the best features, and analyze throughput (TPS) in a performance benchmark.

In our previous posts in this series, we spoke at length about using PgBouncer  and Pgpool-II , the connection pool architecture and pros and cons of leveraging one for your PostgreSQL deployment. In our final post, we will put them head-to-head in a detailed feature comparison and compare the results of PgBouncer vs. Pgpool-II performance for your PostgreSQL hosting !

The bottom line – Pgpool-II is a great tool if you need load-balancing and high availability. Connection pooling is almost a bonus you get alongside. PgBouncer does only one thing, but does it really well. If the objective is to limit the number of connections and reduce resource consumption, PgBouncer wins hands down.

It is also perfectly fine to use both PgBouncer and Pgpool-II in a chain – you can have a PgBouncer to provide connection pooling, which talks to a Pgpool-II instance that provides high availability and load balancing. This gives you the best of both worlds!

Using PgBouncer with Pgpool-II - Connection Pooling Diagram

PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II

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Performance Testing

While PgBouncer may seem to be the better option in theory, theory can often be misleading. So, we pitted the two connection poolers head-to-head, using the standard pgbench tool, to see which one provides better transactions per second throughput through a benchmark test. For good measure, we ran the same tests without a connection pooler too.

Testing Conditions

All of the PostgreSQL benchmark tests were run under the following conditions:

  1. Initialized pgbench using a scale factor of 100.
  2. Disabled auto-vacuuming on the PostgreSQL instance to prevent interference.
  3. No other workload was working at the time.
  4. Used the default pgbench script to run the tests.
  5. Used default settings for both PgBouncer and Pgpool-II, except max_children*. All PostgreSQL limits were also set to their defaults.
  6. All tests ran as a single thread, on a single-CPU, 2-core machine, for a duration of 5 minutes.
  7. Forced pgbench to create a new connection for each transaction using the -C option. This emulates modern web application workloads and is the whole reason to use a pooler!

We ran each iteration for 5 minutes to ensure any noise averaged out. Here is how the middleware was installed:

  • For PgBouncer, we installed it on the same box as the PostgreSQL server(s). This is the configuration we use in our managed PostgreSQL clusters. Since PgBouncer is a very light-weight process, installing it on the box has no impact on overall performance.
  • For Pgpool-II, we tested both when the Pgpool-II instance was installed on the same machine as PostgreSQL (on box column), and when it was installed on a different machine (off box column). As expected, the performance is much better when Pgpool-II is off the box as it doesn’t have to compete with the PostgreSQL server for resources.

Throughput Benchmark

Here are the transactions per second (TPS) results for each scenario across a range of number of clients:

database developer performance postgresql connection control connection pooler connection pooler performance connection queue high availability load balancing number of connections performance testing pgbench pgbouncer pgbouncer and pgpool-ii pgbouncer vs pgpool pgpool-ii pooling modes postgresql connection pooling postgresql limits resource consumption throughput benchmark transactions per second without pooling

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