This is used by the IT department only, …
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- Tech Details
What it's not suited for, is large document stores. This is where PostgreSQL doesn't do well, compared to mongo. however, newer releases show that it is getting there. Genomic data (raw data) is not suited for PostgreSQL. And PostgreSQL engine alone is not suited for timeseries data. But with extensions in place, works really well.
The learning curve is a bit steep compared to MySQL and SQL Server, so might not be suited for a beginner.
Larger queries are able to be obtained quickly. There have been many times when asked for the information STAT and with other applications, I would not have been able to get the data in the time frame given.
PostgreSQL can easily integrated with many platforms we access the database from both our solution engines and the UI.
It is well known and appreciated so relaying on it as our system database can be easily accepted by our customers.
PostgreSQL continues development and support allows us to provide secure and reliable solution acceptable by customer security teams and advisors.
- JSONB data types are great for dealing with various use cases that come up to avoid an EAV pattern.
- Custom data types can be supported.
- Various extensions can really add a lot of excellent features.
- Logical replication in later versions supports per table replication.