hash-db VS graphjin

https://github.com/samsquire/hash-db

I need to combine the ideas in each of these projects into a cohesive solution.

I did some work on trying to implement the YATA algorithm, poorly.

From an SQL database implementation perspective, in my toy Python barebones SQL database that barely supports inner joins (https://github.com/samsquire/hash-db) I tested by testing on postgresql and seeing if my query with two joins produces the same results.

I ought to produce unit tests that prove that tuples from each join operation produces the correct dataset.

For a user perspective, I guess you could write some tooling that loads example data into a database and does an incremental join with each part of the join statement added.

I wrote a toy dynamodb, SQL, Cypher graph and document storage database engine in Python for the learning.

https://github.com/samsquire/hash-db

I am interested in database internals. Btrees come up with regard to designing database systems that are efficient to query on disk. Postgres uses them for its indexes. Radix trees are memory efficient tries which are useful for answering prefix queries. They're also called prefix trees. I use them to get a list of prefixes of a string. Useful for simple intellisense style forms or dynamodb style querying. I've also been studying LSM trees which are used in Leveldb and RocksDB.

I experiment with database technology in my experimental project hash-db https://github.com/samsquire/hash-db The code should be readable.

I need to change my search tree to be self balancing currently it grows to the left or right without balancing. I think I need to use tree rotation depending on which branch has the highest height.

This one looks interesting if you like GraphQL… https://graphjin.com

You're right. Django made a ton of tables, and it's pretty insightful to think about all the stuff it's trying to consider and a nightmare to migrate that framework. Django might have simplified some stuff, but it's still too opaque for my taste and the overall end goals of the project. Currently, I'm testing using graphjin (it doesn't have the best documentation, but it does boast an SQL generation capability that I philosophically think is the best way to do things).

Checkout GraphJin it's an automatic GraphQL to SQL compiler, you write your database queries in GraphQL instead of SQL and it compiles them into efficient SQL on the fly. Works as a library in GO and NodeJS. https://github.com/dosco/graphjin

In GraphJin an automatic GraphQL to SQL compiler we use the gnomock library it startups a database instance (docker) then create the schema and tests data and finally our code connects to it and runs a series of tests. We run these across Mysql, Postgres and a few other DB's. Gnomock supports a wide range of them. Right now we don't take down the db for every test only between test runs but its fast enough that we could. This whole thing runs of a simple `go test -v .` command and we run it on every commit using a githook. https://github.com/dosco/graphjin/blob/master/tests/dbint_te...

This was a bug in GraphJin it has since been fixed. The issue was that you were trying to have multiple subscriptions over a single websocket this did not work (it should) and now it does. https://github.com/dosco/graphjin/commit/43e619b2ff392dd42b99a4d56074a041a54b0e1c

Not exactly GraphQL is just a format to define what data you want back from someplace. You can use it in a browser app to request data from a backend GraphQL server or you can use it as an ORM within your backend app to fetch data from a database using a library like GraphJin. https://github.com/dosco/graphjin