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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. SQL Database As A Service
  5. Amazon RDS for Aurora vs Sequelize

Amazon RDS for Aurora vs Sequelize

OverviewComparisonAlternatives

Overview

Amazon Aurora
Amazon Aurora
Stacks804
Followers744
Votes55
Sequelize
Sequelize
Stacks1.0K
Followers1.4K
Votes143
GitHub Stars30.2K
Forks4.3K

Amazon RDS for Aurora vs Sequelize: What are the differences?

Introduction

Amazon RDS for Aurora and Sequelize are two different tools used in web development. While Amazon RDS for Aurora is a managed relational database service, Sequelize is an Object-Relational Mapping (ORM) library for Node.js. Despite being related to databases, they serve different purposes and have key differences.

  1. Deployment and Management: Amazon RDS for Aurora is a managed service provided by Amazon Web Services (AWS). It handles deployment, scaling, and availability of the database. On the other hand, Sequelize is a library that works with various databases, including Aurora, but it requires manual configuration and management.

  2. Compatibility: Amazon RDS for Aurora is compatible with MySQL and PostgreSQL, allowing existing applications built with these databases to easily migrate to Aurora. Sequelize, on the other hand, is a library that supports multiple databases, including Aurora, MySQL, PostgreSQL, SQLite, and more. It provides compatibility across different database systems.

  3. Performance and Scalability: Amazon RDS for Aurora is highly optimized for performance and scalability. It uses distributed storage and processing, improving read and write speeds. Sequelize, being an ORM library, does not directly impact the performance of the database. However, it provides convenient methods for handling database operations that can be optimized for performance.

  4. Querying and Data Access: Amazon RDS for Aurora allows direct SQL querying using the supported database engines. It provides access to the underlying database engine's features and capabilities. Sequelize, on the other hand, abstracts the database query language and allows developers to interact with the database using JavaScript methods and objects. It provides a higher-level abstraction for querying and data access.

  5. Schema Management: Amazon RDS for Aurora provides automatic schema management, allowing easy creation and modification of database schemas. It handles schema changes seamlessly and simplifies the development workflow. Sequelize, being an ORM library, also provides schema management capabilities. It allows developers to define and modify database schemas using JavaScript models.

  6. Integration and Ecosystem: Amazon RDS for Aurora is tightly integrated with other AWS services, allowing seamless integration within the AWS ecosystem. It provides integration with AWS Lambda, Amazon CloudWatch, and more. Sequelize, being a library, can be used with any Node.js application and integrated with other libraries and frameworks within the Node.js ecosystem.

In summary, Amazon RDS for Aurora is a managed relational database service that simplifies deployment, management, and scalability of databases, while Sequelize is an ORM library that provides an abstraction layer for interacting with databases in Node.js applications. They differ in terms of deployment, management, compatibility, performance, querying, schema management, and integration.

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Detailed Comparison

Amazon Aurora
Amazon Aurora
Sequelize
Sequelize

Amazon Aurora is a MySQL-compatible, relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. Amazon Aurora provides up to five times better performance than MySQL at a price point one tenth that of a commercial database while delivering similar performance and availability.

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.

High Throughput with Low Jitter;Push-button Compute Scaling;Storage Auto-scaling;Amazon Aurora Replicas;Instance Monitoring and Repair;Fault-tolerant and Self-healing Storage;Automatic, Continuous, Incremental Backups and Point-in-time Restore;Database Snapshots;Resource-level Permissions;Easy Migration;Monitoring and Metrics
-
Statistics
GitHub Stars
-
GitHub Stars
30.2K
GitHub Forks
-
GitHub Forks
4.3K
Stacks
804
Stacks
1.0K
Followers
744
Followers
1.4K
Votes
55
Votes
143
Pros & Cons
Pros
  • 14
    MySQL compatibility
  • 12
    Better performance
  • 10
    Easy read scalability
  • 9
    Speed
  • 7
    Low latency read replica
Cons
  • 2
    Vendor locking
  • 1
    Rigid schema
Pros
  • 42
    Good ORM for node.js
  • 31
    Easy setup
  • 21
    Support MySQL & MariaDB, PostgreSQL, MSSQL, Sqlite
  • 14
    Open source
  • 13
    Free
Cons
  • 30
    Docs are awful
  • 10
    Relations can be confusing
Integrations
PostgreSQL
PostgreSQL
MySQL
MySQL
SQLite
SQLite
Microsoft SQL Server
Microsoft SQL Server
Node.js
Node.js
PostgreSQL
PostgreSQL
MySQL
MySQL
MariaDB
MariaDB
io.js
io.js

What are some alternatives to Amazon Aurora, Sequelize?

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

Prisma

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.

Google Cloud SQL

Google Cloud SQL

Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.

Hibernate

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

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.

ClearDB

ClearDB

ClearDB uses a combination of advanced replication techniques, advanced cluster technology, and layered web services to provide you with a MySQL database that is "smarter" than usual.

MikroORM

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

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

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

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.

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