PostgresSQL if the service needs close to 99.999% availability, or more than 1 Gpbs of bandwidth or if the database is expected to grow larger than 100-200GB.

256GB means the SQLite DB can fit in RAM, or the migration will be too slow for the sqlite file and block the service.

It's important to note that with the advent of DuckDB, Parquet and Apache Iceberg, tehre are less and less reasons to stuff your main DB with timeseries data and instead only keep some kind of materialized view and send the raw data to S3.

For everything else, SQLite.

After a few years of using both (see Optimizing SQLite for servers for example), I've found that SQLite particularly shines when used for internal services or public services where a small amount of downtime is tolerable.

So, I choose PostgreSQL (preferably with a managed provider) if the service needs (close to) 100% uptime, if the service needs more than 5 Gbps of bandwidth or if the database is expected to grow larger than 200GB. [...] Bascially, all the situations where running on a single server is not possible.

It's important to note that with the advent of DuckDB, Parquet and Apache Iceberg, there is less and less reasons to stuff your main database with useless junk timeseries data, and instead only keep some kind of materialized view and send the raw data to S3. Thus, there are less and less reasons for your main database to be over 200 GB.

Redis is faster, but they have the same order of magnitude. Maybe +1 order for Postgres in same examples.

The comparison of a lot of data does not made though.

Postgres in web browsers ?!

How to use postgres for everything

The integer used by the Django data model is an Int, but the database used BigInt. The discrepancy occured for the row IDs greater than the maximum value of the int.

Specifically, several tables—including this one—were specified as using an int for their primary key in Django, but used bigint in the real database.

Storing the raw blobs data has one advantage: no data is lost and they can be refined by need.

IDE references can be thrown into postgres in order to retrieve them.

Handling chinese characters in a JSONB column and a dictionnary.

or (of course) temperature changes

An implementation for UUIDv7 was committed to Postgres earlier this month. These have all the benefits of a v4 (random) UUID, but are generated with a more deterministic order using the current time, and perform considerably better on inserts using ordered structures like B-trees.

A list of things to avoid

A nice piece of technology that is developed here

Visualizing and understanding PostgreSQL EXPLAIN plans made easy.

Not sure why this is, but I’m guessing it’s got something to do with working with a schema. It exercises the same sort of brain muscles1 as designing data structures or architecting an application.