PostgreSQL Performance Tuning Tool

What is PostgreSQL performance tuning?

Known for its reliability, feature robustness, and high performance, PostgreSQL is a highly scalable, open-source database management system. Due to the amount of data and users it can accommodate, tuning PostgreSQL is critical for ensuring performance. To effectively optimize performance, database tuning often involves monitoring for deeper visibility into query trends.

Tuning with a PostgreSQL tuning tool can help support your efforts to gain insights more easily with the following features:

• Monitoring: Tuning starts with gathering information through monitoring, so you can more easily pinpoint impacted resources. This includes insight into CPU, I/O, memory, network, and other key factors.
• Troubleshooting and diagnostics: Look at configuration and authentication, as well as resource logs and write-ahead logs, to get more insight into where problems could be occurring. 
• Query tuning: You’ll need to find slow queries and rewrite them using best practices.
• Reporting and logging: By using reports and logs, it’s possible to more easily pinpoint when and where something went wrong, so you can tune effectively.

PostgreSQL tuning best practices

When tuning PostgreSQL, the following are common causes of performance issues and potential opportunities where tuning can help drive significant database performance improvements:

• Check your indexes: Look at the number of indexes you’ve defined on your table and determine whether their potential query benefits outweigh the storage and insert overhead. Every system is different, so the number of indexes is up to your best judgment.
• Avoid using UNIQUE keys and foreign key (FK) constraints: If a UNIQUE constraint is otherwise defined, the insert can necessitate an index lookup to determine if the row already exists, which will adversely impact the speed of your INSERT. Similarly, when you have an FK constraint, every INSERT will typically then need to read from your referenced table, which can degrade performance. Consider denormalizing your data instead.
• Reconsider how you’re using disks: Data stored to the WAL can lead to slow disks that impact insert performance. In addition, to avoid bottlenecks, you can increase throughput by using a separate disk (tablespace) for the database's write-ahead log (WAL) and data.

Using a Postgres query tuning tool, you can more easily evaluate whether a table or indexes may not be following PostgreSQL best practices. SolarWinds Database Performance Analyzer (DPA) includes a built-in table tuning advisor designed to list violations and recommend next steps. Some table tuning best practices you can more easily investigate and help solve for with SolarWinds DPA include:

• Determining whether a foreign key is indexed - Indexing each FK can help improve the performance of queries joining the two tables.
• Identifying overlapping indexes - Examining overlapping indexes can help you determine if any can be removed.
• Removing trailing edge columns - Since wide indexes (five or more columns) require more storage, they can increase the cost of index maintenance. 
• Adding defined indexes for the table - However, if the table is very small, an index might not be more efficient than a full table scan.
• Making sure the table has a primary key (PK) - A PK can uniquely identify a record and is necessary to ensure data integrity. If no column or combination of columns provides a unique value, you can add an artificial PK, such as an ID column.

Why is using a PostgreSQL database tuning tool important?

Database tuning can help optimize database environments, so your applications can quickly access the data. Database tuning can also affect your ability to maintain database and application performance, data integrity, and controls.

Since PostgreSQL is an open-source database, it can often be complex and time-consuming to optimize performance. When building out PostgreSQL database queries and applications, you need a way to ensure optimization without the process being time-consuming or difficult.

PostgreSQL database tuning and related tools can provide you with the insights you need to tune more effectively and ultimately ensure more efficient implementations.

What does a PostgreSQL performance tuning tool do?

With a PostgreSQL tuning tool, database admins can observe query performance trends, view code and query changes, and gain insight into impacts from test and production databases using powerful features designed to help pinpoint issues quickly.

PostgreSQL tuning tools can provide “before and after” views of key database elements to allow you to compare performance, understand trends, and identify issues, such as:

• Metrics on system and database health, including operating system-level and DBMS-focused metrics
• Current snapshots and historical data
• Insight into code and query changes
• Information on impacts within test and production databases
• Alerts for when a system goes down or when various thresholds for latency, counts, or resource consumption are crossed

Using a PostgreSQL performance tuning tool with a query analyzer, like SolarWinds Database Performance Analyzer (DPA), can also let you more easily visualize critical Postgres metrics using multi-dimensional query analysis to pinpoint performance issues.

How does PostgreSQL query tuning work in DPA?

SolarWinds Database Performance Analyzer (DPA) offers key features DBAs need for effective PostgreSQL query tuning.

Effective tuning starts with the right metrics. As a PostgreSQL performance tuning tool, DPA is built to collect detailed metrics to help you understand how resources (such as CPU, disk, and memory) are being used at specific points in time. Important metrics include:

• Memory metrics
• Disk metrics
• Network metrics
• Session metrics
• Wait metrics
• Row metrics
• Vacuum metrics
• Checkpoint metrics
• Replication metrics
• Cache eviction metrics

These metrics provided by the PostgreSQL tuning tool in DPA can help reveal what was happening in the rest of your environment during database slowdowns and provide context to help you identify the root cause of performance problems.

Viewing available PostgreSQL performance tuning metrics is designed to be quick and easy in DPA and can be achieved in about four steps from the Resources tab:

1. On the DPA homepage, click a database instance to view detailed information.
2. In the upper-right corner, click the Resources tab.
   The Resources tab displays all available resource metrics for the selected database instance. By default, charts show data for the last hour.
3. To change the time range, click the date range at the top of the page to open the date picker. Then select a predefined period or enter specific dates.
4. To view annotations or information about VMware events (for instances running on a VM), hover over a dot on the line above a chart. These events can sometimes explain changes in resource metrics.

Another key part of the PostgreSQL performance tuning process is table tuning. The SolarWinds DPA PostgreSQL performance tuning tool is built to identify tables that had inefficient queries run against them. This table tuning advisor feature displays aggregated information about the table, the inefficient queries that ran against it, and any existing indexes. This information can help you make more informed decisions about the best course of action.