PostgreSQL is perhaps the most popular open-source database in the world, and its surge over the past decade has been nothing short of remarkable. Its comprehensiveness and reliability grab the attention of large, established organizations. Additionally, it is a free, open-source database management system. This serves as its main selling point among small businesses operating on a budget.
That said, all those advantages don’t come without a flipside. PostgreSQL, like any other mainstream DBMS, has its downsides that every developer should know about in advance. This article will discuss the most common problems PostgreSQL developers face and the best ways to circumvent them.
There isn’t a single database management system that doesn’t experience occasional performance issues. PostgreSQL isn’t prone to these issues, but they happen occasionally, and it is wise for any systems administrator to know how to identify and get rid of them.
Many developers and systems administrators think parameter tuning in postgresql.conf is the only way to eliminate performance issues. While config parameters may be beneficial, they won’t always take you to the root of the problem. In many instances, the problem will ultimately differ from what you focus on.
Some people use the pg_stat_statements view to detect slow queries by looking at their load times. Others prefer PostgreSQL Explain, which is revered for giving a more accurate and inclusive query breakdown. Together with Analyze, the function helps boost PostgreSQL client performance by showing the execution plan generated by PostgreSQL’s planner and displaying the run time.
Replication lag problems
Cases of replication lag issues are few and far between, but their heavy impact on application performance makes them worth including in this list. Identifying PostgreSQL replication lags is a reasonably easy task, but there are several ways of looking at the problem, which might determine the most suitable way to solve it.
PostgreSQL uses streaming replication – a feature introduced in version 9.0 – which should make it fast since changes are logged as a series of log records exactly as the WAL receiver intercepts them. Once these log records are put on the WAL file, the PostgreSQL startup process replays that data, and the streaming replication process begins.
Most lags occur when the WAL segment cannot be found or there are network issues, configuration problems, bad hardware, or busy nods. You can use the pg_stat_replication utility to get a view of the streaming replication status. ClusterControl has also been shown to assist with database node monitoring.
Downtime when updating the schema
Updating a PostgreSQL database schema is easy if you can go offline while doing it. You just need to close the application, build a schema backup, perform the update operations, review and test your work, and restart your application, hoping you got everything right.
However, things won’t be so easy if the nature of your application calls for zero downtime. This requires a complex, multi-phase procedure that may involve using a backward-compatible approach to change your database. The point of this is to make the database usable to both your old and new application versions.
For migration operations that are not backward-compatible, you can break them down into smaller steps to create a database that both versions of your application can use. Often, that requires the user to create a new table or view, or column, which your new application version will use.
First of all, let it be clear that the PostgreSQL database offers some of the best data security features for your server and data. The problem comes in when it is time to identify and deploy them.
Security hardening in PostgreSQL can be divided into three categories: server configuration, data encryption, and network configuration. It is always advisable to perform data encryption in-flight and at rest. For in-flight data encryption, client database access must be set to use SSL. The server should also require or accept secure connections.
At-rest encryption can be performed at many different phases of the stack; where you implement it will be primarily determined by infrastructure and application requirements. The pgcrypto module is used for encryption and decryption purposes at the database level. The technique is helpful as a last resort when there is no other viable encryption method, and specific sets of data must be encrypted.
Administrators can always encrypt data at the cloud or file system levels – an approach that is more seamless and less impactful on performance.
The risk of data loss
While there are many ways to trim the risk of data loss, you can never reduce that possibility to zero. Thus, every database administrator must have a robust backup strategy to ensure applications are back up and running as soon as possible following a cyber-attack, a catastrophic event, or a data integrity issue.
Data backups should be at the center of any database management strategy. For PostgreSQL users, there are several ways to set up a backup strategy, depending on preferences and other functional factors. For example, the inbuilt pg_dump function can be used to build periodic backups with virtual machine installation or bare metal in the absence of a managed service layer. The pg_dump output is made up of a text file that you can store in a platform not attached to the database and retrieve later when the chips are down. The data recovery operation is usually simply about making the file available to the PostgreSQL program as input.
While using pg_dump is great for user-formulated backup plans, cloud services such as Stratoscale SMD and AWS RDS provide backup and disaster recovery as built-in features, so you don’t have to worry about building a backup strategy from scratch.
Database management is only simple if you get the planning phase right and are acquainted with everyday challenges and viable mitigation strategies. Hopefully, the above tips will help you brace for snags and get back up quickly and seamlessly.