buntdb
GORM
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buntdb
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PostgreSQL: No More Vacuum, No More Bloat
Experimental format to help readability of a long rant:
1.
According to the OP, there's a "terrifying tale of VACUUM in PostgreSQL," dating back to "a historical artifact that traces its roots back to the Berkeley Postgres project." (1986?)
2.
Maybe the whole idea of "use X, it has been battle-tested for [TIME], is robust, all the bugs have been and keep being fixed," etc., should not really be that attractive or realistic for at least a large subset of projects.
3.
In the case of Postgres, on top of piles of "historic code" and cruft, there's the fact that each user of Postgres installs and runs a huge software artifact with hundreds or even thousands of features and dependencies, of which every particular user may only use a tiny subset.
4.
In Kleppmann's DDOA [1], after explaining why the declarative SQL language is "better," he writes: "in databases, declarative query languages like SQL turned out to be much better than imperative query APIs." I find this footnote to the paragraph a bit ironic: "IMS and CODASYL both used imperative query APIs. Applications typically used COBOL code to iterate over records in the database, one record at a time." So, SQL was better than CODASYL and COBOL in a number of ways... big surprise?
Postgres' own PL/pgSQL [2] is a language that (I imagine) most people would rather NOT use: hence a bunch of alternatives, including PL/v8, on its own a huge mass of additional complexity. SQL is definitely "COBOLESQUE" itself.
5.
Could we come up with something more minimal than SQL and looking less like COBOL? (Hopefully also getting rid of ORMs in the process). Also, I have found inspiring to see some people creating databases for themselves. Perhaps not a bad idea for small applications? For instance, I found BuntDB [3], which the developer seems to be using to run his own business [4]. Also, HYTRADBOI? :-) [5].
6.
A usual objection to use anything other than a stablished relational DB is "creating a database is too difficult for the average programmer." How about debugging PostgreSQL issues, developing new storage engines for it, or even building expertise on how to set up the instances properly and keep it alive and performant? Is that easier?
I personally feel more capable of implementing a small, well-tested, problem-specific, small implementation of a B-Tree than learning how to develop Postgres extensions, become an expert in its configuration and internals, or debug its many issues.
Another common opinion is "SQL is easy to use for non-programmers." But every person that knows SQL had to learn it somehow. I'm 100% confident that anyone able to learn SQL should be able to learn a simple, domain-specific, programming language designed for querying DBs. And how many of these people that are not able to program imperatively would be able to read a SQL EXPLAIN output and fix deficient queries? If they can, that supports even more the idea that they should be able to learn something different than SQL.
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1: https://dataintensive.net/
2: https://www.postgresql.org/docs/7.3/plpgsql-examples.html
3: https://github.com/tidwall/buntdb
4: https://tile38.com/
5: https://www.hytradboi.com/
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Is there a nice embedded json db, like PoloDB (Rust) for Golang
https://github.com/tidwall/buntdb -> i think this one you might want
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Open Source Databases in Go
buntdb - Fast, embeddable, in-memory key/value database for Go with custom indexing and spatial support.
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Alternative to MongoDB?
BuntDB for NoSQL
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Path hints for B-trees can bring a performance increase of 150% – 300%
BuntDB [0] from @tidwall uses this package as a backing data structure. And BuntDB is in turn used by Tile38 [1]
[0] https://github.com/tidwall/buntdb
- The start of my journey learning Go. Any tips/suggestions would greatly appreciated!
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In-memory caching solutions
I've used BuntDB and had a great experience with it. It's basically just a JSON-based key-value store. I'm a huge fan of the developers other work (sjson, gjson, jj, etc) and stumbled on it while looking for a simple, embedded DB solution. It's not specifically a cache, though--just a simple DB, so you'd have to write the caching logic yourself.
GORM
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Go ORMs Compared
GORM is a comprehensive ORM tool in Go, offering a code-first approach which allows defining database schemas using struct tags in Go. It's known for its developer-friendly nature, making it suitable for both beginners and experienced users. GORM supports a variety of SQL databases like MySQL, PostgreSQL, and SQLite. It's designed to be flexible, allowing developers to drop down to raw SQL when necessary. However, it's important to be cautious about its performance implications in large-scale applications.
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6 🔥 Awesome Golang packages (web devs)
Homepage: https://gorm.io/
- Tenha controle sobre seu SQL com Golang e SQLC
- Não use funções puras com Go
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Build an Event-Driven Uptime Monitor in Go 🚀
Since most of these APIs will be simple CRUD (Create/Read/Update/Delete) endpoints, let's build this service using GORM, an ORM library that makes building CRUD endpoints really simple.
- [OpenSource] I am building high performance Plex alternative in Go for Movies and TV Show
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Building Robust Applications in Go: Integrating Envconfig, Gorm, and OpenSearch
After successfully configuring the application, it's time to delve into integrating the data layer. For this purpose, I will utilize gorm, a powerful SQL ORM that facilitates rapid development of the data layer using model structs.
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ORM or no ORM that is the question
For basic INSERT ... VALUES ... or SELECT ... WHERE ... JOIN ..., use a library such as GORM. For INSERT .... SELECT ... statements where one combines two round trips (SELECT and INSERT) into one, ORMs have a hard time performing this query. Particularly when you start doing joins. Joins are the heart of Relational database theory (they denote relationships). So get to know what an INNER, LEFT, RIGHT and OUTER join is and why you would use them. Also learn INSERT ... SELECT ...
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Why ORMs are so hated?
I have never hated gorm and it serves me well. However I tend to feed it raw SQL very often.
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Golang RESTAPI boilerplate repository
Array of values with embedded value all pointed to the last value, reflect code was broken: https://github.com/go-gorm/gorm/pull/5901 data corruption
What are some alternatives?
bolt
ent - An entity framework for Go
badger - Fast key-value DB in Go.
Xorm
nutsdb - A simple, fast, embeddable, persistent key/value store written in pure Go. It supports fully serializable transactions and many data structures such as list, set, sorted set.
SQLBoiler - Generate a Go ORM tailored to your database schema.
go-memdb - Golang in-memory database built on immutable radix trees
go-pg - Golang ORM with focus on PostgreSQL features and performance
goleveldb - LevelDB key/value database in Go.
pgx - PostgreSQL driver and toolkit for Go
ledisdb - A high performance NoSQL Database Server powered by Go
beego orm