GORM vs Jugglingdb

Overview

Jugglingdb

Stacks5

Followers8

Votes0

GitHub Stars2.0K

Forks239

GORM

Stacks193

Followers128

Votes0

GitHub Stars657

Forks194

GORM vs Jugglingdb: What are the differences?

## Key Differences between GORM and Jugglingdb 

1. **Database Support**: GORM is primarily focused on supporting the SQL database while Jugglingdb has broader support for various databases such as MongoDB, CouchDB, Redis, and more.

2. **Model Definition**: In GORM, models are defined using struct tags in Go language, making it simple and intuitive. On the other hand, Jugglingdb uses a separate modeling language called jugglingdb schema, which can be more verbose and complex for some developers.

3. **Relationship Handling**: GORM provides robust support for defining and handling relationships between models using various types like `hasOne`, `hasMany`, and more. In contrast, Jugglingdb offers a more abstract approach to relationships, which may require more effort in implementation.

4. **Performance**: GORM is well-known for its performance optimization techniques, such as lazy loading, caching, and prefetching, to enhance the overall speed and efficiency of database operations. Jugglingdb, while capable, may not have the same level of performance optimization features as GORM.

5. **Community and Support**: GORM has a larger and more active community of developers, leading to frequent updates, bug fixes, and a rich ecosystem of plugins and extensions. Jugglingdb, while supported by a dedicated community, may not have the same level of community engagement and breadth of resources.

6. **Documentation**: GORM provides comprehensive and well-structured documentation, making it easier for developers to learn and use the framework efficiently. Jugglingdb, on the other hand, may have less extensive or organized documentation, which can pose challenges for new users in understanding and utilizing its features.

In Summary, GORM and Jugglingdb differ in database support, model definition, relationship handling, performance optimization, community support, and documentation.

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CLI (Node.js)

Manual

Detailed Comparison

Jugglingdb	GORM
JugglingDB(3) is cross-db ORM for nodejs, providing common interface to access most popular database formats. Currently supported are: mysql, sqlite3, postgres, couchdb, mongodb, redis, neo4j and js-memory-storage (yep, self-written engine for test-usage only). Jugglingdb also works on client-side (using WebService and Memory adapters), which allows to write rich client-side apps talking to server using JSON API.	It is a fantastic ORM library for Golang, aims to be developer friendly. It is an ORM library for dealing with relational databases. This library is developed on top of database/sql package.
-	Full-Featured ORM; Associations (has one, has many, belongs to, many to many, polymorphism, single-table inheritance); Hooks (before/after create/save/update/delete/find); Eager loading with Preload, Joins; Transactions, Nested Transactions, Save Point, RollbackTo to Saved Point; Context, Prepared Statment Mode, DryRun Mode; Batch Insert, FindInBatches, Find/Create with Map, CRUD with SQL Expr and Context Valuer; SQL Builder, Upsert, Locking, Optimizer/Index/Comment Hints, Named Argument, SubQuery; Composite Primary Key, Indexes, Constraints; Auto Migrations; Logger; Extendable, flexible plugin API
Statistics
GitHub Stars 2.0K	GitHub Stars 657
GitHub Forks 239	GitHub Forks 194
Stacks 5	Stacks 193
Followers 8	Followers 128
Votes 0	Votes 0
Integrations
No integrations available	MongoDB Jenkins Spring Boot Groovy

What are some alternatives to Jugglingdb, GORM?

Sequelize

Sequelize is a promise-based ORM for Node.js and io.js. It supports the dialects PostgreSQL, MySQL, MariaDB, SQLite and MSSQL and features solid transaction support, relations, read replication and more.

Prisma

Prisma is an open-source database toolkit. It replaces traditional ORMs and makes database access easy with an auto-generated query builder for TypeScript & Node.js.

Hibernate

Hibernate is a suite of open source projects around domain models. The flagship project is Hibernate ORM, the Object Relational Mapper.

Doctrine 2

Doctrine 2 sits on top of a powerful database abstraction layer (DBAL). One of its key features is the option to write database queries in a proprietary object oriented SQL dialect called Doctrine Query Language (DQL), inspired by Hibernates HQL.

MikroORM

TypeScript ORM for Node.js based on Data Mapper, Unit of Work and Identity Map patterns. Supports MongoDB, MySQL, MariaDB, PostgreSQL and SQLite databases.

Entity Framework

It is an object-relational mapper that enables .NET developers to work with relational data using domain-specific objects. It eliminates the need for most of the data-access code that developers usually need to write.

peewee

A small, expressive orm, written in python (2.6+, 3.2+), with built-in support for sqlite, mysql and postgresql and special extensions like hstore.

MyBatis

It is a first class persistence framework with support for custom SQL, stored procedures and advanced mappings. It eliminates almost all of the JDBC code and manual setting of parameters and retrieval of results. It can use simple XML or Annotations for configuration and map primitives, Map interfaces and Java POJOs (Plain Old Java Objects) to database records.

Entity Framework Core

It is a lightweight, extensible, open source and cross-platform version of the popular Entity Framework data access technology. It can serve as an object-relational mapper (O/RM), enabling .NET developers to work with a database using .NET objects, and eliminating the need for most of the data-access code they usually need to write.

SQLAlchemy

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL.

Related Comparisons

GORM vs Jugglingdb: What are the differences?

## Key Differences between GORM and Jugglingdb 

1. **Database Support**: GORM is primarily focused on supporting the SQL database while Jugglingdb has broader support for various databases such as MongoDB, CouchDB, Redis, and more.

2. **Model Definition**: In GORM, models are defined using struct tags in Go language, making it simple and intuitive. On the other hand, Jugglingdb uses a separate modeling language called jugglingdb schema, which can be more verbose and complex for some developers.

3. **Relationship Handling**: GORM provides robust support for defining and handling relationships between models using various types like `hasOne`, `hasMany`, and more. In contrast, Jugglingdb offers a more abstract approach to relationships, which may require more effort in implementation.

4. **Performance**: GORM is well-known for its performance optimization techniques, such as lazy loading, caching, and prefetching, to enhance the overall speed and efficiency of database operations. Jugglingdb, while capable, may not have the same level of performance optimization features as GORM.

5. **Community and Support**: GORM has a larger and more active community of developers, leading to frequent updates, bug fixes, and a rich ecosystem of plugins and extensions. Jugglingdb, while supported by a dedicated community, may not have the same level of community engagement and breadth of resources.

6. **Documentation**: GORM provides comprehensive and well-structured documentation, making it easier for developers to learn and use the framework efficiently. Jugglingdb, on the other hand, may have less extensive or organized documentation, which can pose challenges for new users in understanding and utilizing its features.

In Summary, GORM and Jugglingdb differ in database support, model definition, relationship handling, performance optimization, community support, and documentation.

GORM vs Jugglingdb

Overview