Performance

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Performance is an important goal for [pgagroal][pgagroal] and effort have been made to make [pgagroal][pgagroal] scale and use a limited number of resources.

This chapter describes [pgagroal][pgagroal] performance characteristics and provides benchmarking results compared to other [PostgreSQL][postgresql] connection pool implementations.

Benchmarking Methodology

The [pgbench][pgbench] program was used in the performance runs. All pool configurations were made with performance in mind.

The runs were performed on [RHEL][rhel] 7.7 / EPEL / DevTools 8 based machines on 10G network. All connection pools were the latest versions as of January 14, 2020. [pgagroal][pgagroal] was using the epoll mode of [libev][libev].

Performance Results

Simple Protocol

This run uses:

pgbench -M simple

Extended Protocol

This run uses:

pgbench -M extended

Prepared Statements

This run uses:

pgbench -M prepared

Read-Only Workload

This run uses:

pgbench -S

Performance Tuning

Pipeline Selection

Choose the appropriate pipeline for your workload:

• Performance pipeline: Fastest option for high-throughput scenarios
• Session pipeline: Balanced performance with full feature support
• Transaction pipeline: Best for applications with many short transactions

See Pipelines for detailed configuration.

Connection Pool Sizing

Optimal pool sizing depends on your workload:

• CPU-bound workloads: Pool size approximately equals number of CPU cores
• I/O-bound workloads: Pool size can be higher than CPU cores
• Mixed workloads: Start with 2x CPU cores and adjust based on monitoring

System-Level Optimizations

Network Configuration

• Use dedicated network interfaces for database traffic
• Configure appropriate TCP buffer sizes
• Consider using 10G or higher network speeds for high-throughput scenarios

Memory Configuration

• Enable huge pages for better memory management
• Configure appropriate shared memory settings
• Monitor memory usage patterns

CPU Configuration

• Pin pgagroal processes to specific CPU cores if needed
• Configure CPU governor for performance
• Monitor CPU utilization patterns

Monitoring Performance

Use the following metrics to monitor pgagroal performance:

• Connection utilization: Active vs. total connections
• Response times: Average and percentile response times
• Throughput: Transactions per second
• Resource usage: CPU, memory, and network utilization

See Prometheus for detailed monitoring setup.