Do You Even Need a Database? - DB Pro Blog

We built the same HTTP server in Go, Bun, and Rust using two storage strategies: read the file on every request, or load everything into memory. Then we ran real benchmarks. The results are more interesting than you'd expect.

At some point, don't you just end up making a low-quality, poorly-tested reinvention of SQLite by doing this and adding features?
Sometimes yes, I've seen it. It even tends to happen on NoSQL databases as well. Three times I've seen apps start on top of Dynamo DB, and then end up re-implementing relational databases at the application level anyway. Starting with postgres would have been the right answer for all three of those. Initial dev went faster, but tech debt and complexity quickly started soaking up all those gains and left a hard-to-maintain mess.

This always confuses me because we have decades of SQL and all its issues as well. Hundreds of experienced devs talking about all the issues in SQL and the quirks of queries when your data is not trivial.

One would think that for a startup of sorts, where things changes fast and are unpredictable, NoSQL is the correct answer. And when things are stable and the shape of entities are known, going for SQL becomes a natural path.

There is also cases for having both, and there is cases for graph-oriented databases or even columnar-oriented ones such as duckdb.

Seems to me, with my very limited experience of course, everything leads to same boring fundamental issue: Rarely the issue lays on infrastructure, and is mostly bad design decisions and poor domain knowledge. Realistic, how many times the bottleneck is indeed the type of database versus the quality of the code and the imlementation of the system design?

Disclaimer: I work part time on the DB team.

You could also consider renting an Oracle DB. Yep! Consider some unintuitive facts:

• It can be cheaper to use Oracle than MongoDB. There are companies that have migrated away from Mongo to Oracle to save money. This idea violates some of HN's most sacred memes, but there you go. Cloud databases are things you always pay for, even if they're based on open source code.

• Oracle supports NoSQL features including the MongoDB protocol. You can use the Mongo GUI tools to view and edit your data. Starting with NoSQL is very easy as a consequence.

• But... it also has "JSON duality views". You start with a collection of JSON documents and the database not only works out your JSON schemas through data entropy analysis, but can also refactor your documents into relational tables behind the scenes whilst preserving the JSON/REST oriented view e.g. with optimistic locking using etags. Queries on JSON DVs become SQL queries that join tables behind the scenes so you get the benefits of both NoSQL and SQL worlds (i.e. updating a sub-object in one place updates it in all places cheaply).

• If your startup has viral growth you won't have db scaling issues because Oracle DBs scale horizontally, and have a bunch of other neat performance tricks like automatically adding indexes you forgot you needed, you can materialize views, there are high performance transactional message queues etc.

So you get a nice smooth scale-up and transition from ad hoc "stuff some json into the db and hope for the best" to well typed data with schemas and properly normalized forms that benefit from all the features of SQL.

Good points, but Postgres has all those, along with much better local testing story, easier and more reliable CDC, better UDFs (in Python, Go etc.), a huge ecosystem of extensions for eg. GIS data, no licencing issues ever, API compatability with DuckDB, Doris and other DBs, and (this is the big one) is not Oracle.