I'd say this project is rather useful in that it made queries far much more intuitive, something SQL aimed for in 1970s but eventually fails: for simple ones like `SELECT type_1 FROM roles;` it is indeed intuitive, but for something a little bit complicated, that intuitiveness quickly fall apart:
```sql
SELECT DISTINCT type_1 FROM roles AS r1
WHERE NOT EXISTS(
SELECT * FROM roles AS r2
WHERE r2.type_1 = r1.type_1
AND r2.legendary = 'True'
);
```
This queries all "`TYPE_1`s that all characters in this type are not legendary", and it is near impossible for a newcomer who had never learnt about SQL before to figure out the query, yet typing the sentence in quotes in `Vizly` gives exactly what is needed. Sure it took 1 minute to execute (which is probably why some thought it is down), but formulating the above SQL statement took much longer, and I am not sure that statement even works (I haven't touched SQL for quite some time).
Unfortunately, Google seemed to have developed its own multi-dimensional array library as well, featuring virtual views, handling of large arrays that cannot fit into main memory, compression and more: https://github.com/google/tensorstore https://ai.googleblog.com/2022/09/tensorstore-for-high-perfo...
What are `librapid`'s strengths and unique features compared to Google's `Tensor Store`? Being lightweight might be one.