It's almost always going to be faster to perform all of these operations in PostgreSQL. These database systems have been designed to scale well for huge amounts of data, and are highly optimised for their typical use cases. For example, they don't have to load all of the data from disk to perform most basic filters^[1].

Even if this were not the case, the network latency / usage alone world be enough to balance this out, especially if you were running the query often.

Actually, if you are comparing data that is already loaded into memory to data being retrieved from a database, then the in-memory operations are often going to be faster. Databases have overhead:

• They are in separate processes on the same server or on a different server, so data and commands needs to move between them.
• Queries need to be parsed and optimized.
• Databases support multiple users, so other work may be going on using up resources.
• Databases maintain ACID properties and data integrity, which can add additional overhead.

The first two of these in particular add overhead compared to equivalent in-memory operations for every query.

That doesn't mean that databases do not have advantages, particularly for complex queries:

• They implement multiple different algorithms and have an optimizer to choose the best one.
• They can take advantage of more resources -- particularly by running in parallel.
• They can (sometimes) cache results saving lots of time.

The advantage of databases is not that they provide the best performance all the time. The advantage is that they provide good performance across a very wide range of requests with a simple interface (even if you don't like SQL, I think you need to admit that it is simpler, more concise, and more flexible that writing code in a 3rd generation language).

In addition, databases protect data, via ACID properties and other mechanisms to support data integrity.