jOOQ VS TypeORM

> 2. ORMs do not hide SQL nastiness.

This is certainly true!

I mean: ORMs are now well known to "make the easy queries slightly more easy, while making intermediate queries really hard and complex queries impossible".

I think the are of ORMs is over. It simply did not deliver.

If a book on SQL is --say-- 100 pages, a book on Hibernate is 400 pages. So much to learn just to make the easy queries slightly easier to type? Just not worth it.

I prefer jooq any day over ORMs. And dont get me started over what tools like Hasuna have to offer.

There are also some languages (forgot the names) that are SQL-done-right. Select in the back, more type safe, more logic, more in the same steps as the query gets executed. These need to be adopted by PG and MySQL and we're good to go. (IMHO)

https://www.jooq.org/

https://hasura.io/

See: https://github.com/jOOQ/jOOQ/issues/5916

I've worked on a few systems that were stored procedure heavy with Microsoft SQL server, not so much because I am a .NET guy, some of these came when I was working on super-random projects for a consulting company.

My take is that it is a lot like building a system that has an API over the database except that instead of writing in API in, say, Java and exposing it through an http API with, say, JAX-RS, you are writing the API in stored procedures and accessing it through JDBC or ODBC or the native API of the database.

It seems very possible to build some thin layer that uses metadata to make an http API over stored procedures.

I'd say that systems like that can work very well.

The basic challenge is maintaining version control over your scripts, my coworkers were rubyists on my first such project and built a system inspired by migrations in Ruby on Rails where we wrote up and down migration scripts for every database change. I carried that approach to other projects where the people had less discipline to begin with. There is a little awkwardness there that the "down" script that reverts a procedure to a previous version has a cut-and-pasted copy of the old version of the stored procedure, if I had to do it over again I'd make something where each version of a stored proc is in a numbered file and the "migrations" just say "upgrade ABC proc to version 7" or maybe you could make something that looks into the VCS and finds the old version.

From what I've read, PL/SQL from Oracle looks a lot better than the Transact-SQL language in SQL server but I've never done a major project with Oracle. Most places I've worked at recently use PostgreSQL and I think this would be a viable architecture for that.

One area where it seems to be a hassle is with the "query builder" pattern, for instance where I work now we have a very complex search form with a huge number of options that builds a SQL query. I think you can do that kind of thing with what they call "Dynamic SQL", see

https://www.postgresql.org/docs/15/plpgsql-statements.html#P...

but it seems preferable to do that kind of thing with a real programming language, particularly if you have tools like

https://www.jooq.org/

I have a bachelor's in computer science, took a databases class in college (which I did poorly in), and worked as a backend developer for two years, but I always struggled with SQL. I can do the basic SELECT * FROM table WHERE column = 1 but when the SQL statement gets long with lots of joins I couldn't understand it and relied on another programmer for help. When I need to build a website myself I end up going with MongoDB because that allows me to write code instead of writing SQL. That being said, instead of doing all the data processing stuff in the backend, I'd like to try doing as much of it as I can in the database and learn some programmimg language that is SQL-esque (for my next personal project). I know Scala and am very comfortable doing functional programming stuff like List(1,2,3).filter(_.isEven()) to get the even numbers in a list or writing List(1,2,3).reduce(_+_) to apply the addition operation on all the numbers in a list. I know the Big Data framework Apache Spark is written in and works with Scala, but I really want to learn something that works with a traditional database that runs on one centralized server and not have to worry about the distributed computing MapReduce paradigm stuff (also installing the Big Data ecosystem on my personal computer is a pain). Like I want to try building something with a traditional database like Oracle, SQL Server, etc. Something I find really helpful is having IDE code error highlighting and auto-completion and the ability to run a static analysis code quality checker tool, which I can do with Scala code, but I don't know of a way to have those things with traditional SQL Strings sent from the backend to the database. I know of things like Java's JOOQ or C#'s LINQ, but I don't want to use one of those, I want to use something in the database that is database specific and pushes as much data processing as possible into the database. I heard of languages like PL/SQL, T-SQL, and PL/pgSQL to add procedural control to SQL, making it like a real programming language. On Wikipedia I found this list of PL/SQL editors but there are so many choices and I don't know which one to pick (it has to not cost me money and I would love one that has auto-completion with error highlighting and suggestions or maybe some sort of graphical query builder tool that gives me choices of what to put to compose my statement). I saw someone on Reddit say that more recently they added the ability to add database triggers in various programming languages. I also heard mentions online of this thing called "dbt" which adds software engineering tools like version control to SQL, but I don't know if that can help me get around my difficulty with SQL or if it is something I would want to use. Any advice would be appreciated.

Spring Boot, ili ako bi nesto vise lightweight u Javi Spark + jOOQ

> I've been doing ORM on Java since Hibernate was new, and it has always sucked.

Have you ever looked at something like myBatis? In particular, the XML mappers: https://mybatis.org/mybatis-3/dynamic-sql.html

Looking back, I actually quite liked it - you had conditionals and ability to build queries dynamically (including snippets, doing loops etc.), while still writing mostly SQL with a bit of XML DSL around it, which didn't suck as much as one might imagine. The only problem was that there was still writing some boilerplate, which I wasn't the biggest fan of.

Hibernate always felt like walking across a bridge that might collapse at any moment (one eager fetch away from killing the performance, or having some obscure issue related to the entity mappings), however I liked tooling that let you point towards your database and get a local set of entities mapped automatically, even though codegen also used to have some issues occasionally (e.g. date types).

That said, there's also projects like jOOQ which had a more code centric approach, although I recall it being slightly awkward to use in practice: https://www.jooq.org/ (and the autocomplete killed the performance in some IDEs because of all the possible method signatures)

More recently, when working on a Java project, I opted for JDBI3, which felt reasonably close to what you're describing, at the expense of not being able to build dynamic queries as easily, as it was with myBatis: https://jdbi.org/

That said, with the multi-line string support we have in Java now, it was rather pleasant regardless: https://blog.kronis.dev/tutorials/2-4-pidgeot-a-system-for-m...

I don't think there's a silver bullet out there, everything from lightweight ORMs, to heavy ORMs like Hibernate, or even writing pure SQL has drawbacks. You just have to make the tradeoffs that will see you being successful in your particular project.

Have a look at jooq - I know this has been used to rewrite SQL from one dialect to another, so it MUST be capable of collating code activity metrics. Look here. Otherwise, you might want to look into writing your own parser. ANTLR has a T-SQL dialect parser script here.

Feature requests go here: https://github.com/jOOQ/jOOQ/issues/new/choose. Looking forward!

You may have the fortune of being familiar with the jOOQ library for Java/JVM apps, that can generate domain models based on your database schema, as well as methods on these classes to perform queries. In case you're not, here an example Postgres schema:

If you use Sequalize, TypeORM or for MongoDB, we have Mongoose these types of ORM tools, then you are safe by default because these help us against the SQL query injection attacks by default.

We decided to use MySQL for a database. and TypeOrm for ORM. The ER diagram is provided below. For example, the task_assignments table holds information about user assignments to tasks. While in DDD, there is a pattern to design denormalized tables that reflect the structure of domain objects more directly, but this time, a more conventional table design was chosen. TypeOrm models:

How does this compare to using directly an ORM lib that supports browser like TypeORM [0] via SQL.js [1]?

[0] https://typeorm.io/

* Patch a third-party library that was setting an HTTP header to `null`. NodeJS handles this case just fine, but Deno throws an error [2].

After all of that work, I finally was able to use Deno in my project. It was really cool! Unfortunately, both VS Code and IntelliJ with Deno are essentially unusable [3]. Or, at least, unacceptably slow compared to what I had with NodeJS.

[0]: https://stackoverflow.com/a/66073607

[1]: https://github.com/typeorm/typeorm/issues/6123#issuecomment-...

[2]: https://github.com/Sansossio/twisted/issues/97

[3]: https://github.com/denoland/vscode_deno/issues/895

TypeORM is a very convenient ORM for JS apps. We use it with NestJS and running it on NodeJS.

We are going to start using TypeORM as an ORM to help us interact with Postgres, but we also have an example of using Prisma in the future and everything that we have to adapt to switch the ORMs if necessary. At the end we are implementing neon.tech as a production database, right? 😉

TypeORM is a popular Object-Relational Mapping (ORM) library for Node.js. It provides a high-level abstraction over relational databases, making it easy to perform CRUD (Create, Read, Update, Delete) operations.

TypeORM places its focus on TypeScript and JavaScript (ES7+) development. It offers compatibility with various database systems, including MySQL, PostgreSQL, SQLite, and MongoDB. What sets TypeORM apart is its robust integration with TypeScript. It provides a user-friendly experience with a convenient decorator-based syntax for defining entities and relationships. Additionally, TypeORM supports the repository pattern and enables eager loading, enhancing its versatility for developers.

ᴬ typeorm officially supports mssql@v9, but the support for the custom stream builder was added in mssql@v10. Since mssql is a peer dependency of typeorm, you can force override it and use the Cloud SQL Connector with typeorm. There is an open PR to add support for mssql@v10 in typeorm.