Re: Where **not** to use PostgreSQL?

Hard question.  There are a lot of general places where PostgreSQL is not by itself the best fit, and where a careful weighing of pros and cons would need to be made before deciding to use it.

Having used PostgreSQL in place of ElasticSearch for PB-scale deployments, as a high-throughput queue system, and near-real-time OLAP workloads, I am fairly aware of how hard it can be pushed.

So the answers here are not "don't use PostgreSQL here" but "think about it first and consider alternatives."

 

Replacing with "What would you consider to be the tradeoffs?" 

So a few possibilities:

1.  a) TB-scale full text search systems.

     b) PostgreSQL's full text search is quite capable but not so powerful that it can completely replace Lucene-based systems.  So you have to consider complexity vs functionality if you are tying with other data that is already in PostgreSQL.  Note further that my experience with at least ElasticSearch is that it is easier to scale something built on multiple PostgreSQL instances into the PB range than it is to scale ElasticSearch into the PB range.

     c) Solr or ElasticSearch

2.  a) High performance job queues

     b) PostgreSQL index and table structures are not well suited to large numbers of ordered deletes.  There are ways around these problems and again if other data is in PostgreSQL, the tradeoff is around transactional behavior and complexity there vs ease of scaling performance.

     c) Redis if the job queue easily fits into a small enough amount of memory, or Kafka if it does not

On to where you actually should never use PostgreSQL:

Don't use PostgreSQL for things where you do not want or cannot guarantee transactional atomicity.  

While it is possible to have untrusted languages have side effects in the real world, the fact is that mixing transactions and non-transactional behavior in this way adds a lot of really ugly complexity.

Use another development environment instead.