Amazon RDS for Aurora vs Sequelize

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Amazon RDS for Aurora
Amazon RDS for Aurora

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Sequelize
Sequelize

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

Amazon RDS for Aurora: MySQL and PostgreSQL compatible relational database with several times better performance. 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: Easy-to-use multi sql dialect ORM for Node.js & io.js. 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.

Amazon RDS for Aurora and Sequelize are primarily classified as "SQL Database as a Service" and "Object Relational Mapper (ORM)" tools respectively.

"MySQL compatibility " is the primary reason why developers consider Amazon RDS for Aurora over the competitors, whereas "Good ORM for node.js" was stated as the key factor in picking Sequelize.

Sequelize is an open source tool with 18.9K GitHub stars and 2.99K GitHub forks. Here's a link to Sequelize's open source repository on GitHub.

According to the StackShare community, Amazon RDS for Aurora has a broader approval, being mentioned in 116 company stacks & 30 developers stacks; compared to Sequelize, which is listed in 38 company stacks and 33 developer stacks.

- No public GitHub repository available -

What is Amazon RDS for Aurora?

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.

What is 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.
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Why do developers choose Amazon RDS for Aurora?
Why do developers choose Sequelize?

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    What are some alternatives to Amazon RDS for Aurora and Sequelize?
    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.
    Google Cloud SQL
    MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don’t run out of space and give your application the redundant, reliable storage it needs.
    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.
    DigitalOcean Managed Databases
    Build apps and store data in minutes with easy access to one or more databases and sleep better knowing your data is backed up and optimized.
    Azure Database for MySQL
    Azure Database for MySQL provides a managed database service for app development and deployment that allows you to stand up a MySQL database in minutes and scale on the fly – on the cloud you trust most.
    See all alternatives
    Decisions about Amazon RDS for Aurora and Sequelize
    Tim Specht
    Tim Specht
    ‎Co-Founder and CTO at Dubsmash · | 13 upvotes · 57.4K views
    atDubsmashDubsmash
    Amazon RDS for Aurora
    Amazon RDS for Aurora
    Redis
    Redis
    Amazon DynamoDB
    Amazon DynamoDB
    Amazon RDS
    Amazon RDS
    Heroku
    Heroku
    PostgreSQL
    PostgreSQL
    #PlatformAsAService
    #Databases
    #NosqlDatabaseAsAService
    #SqlDatabaseAsAService

    Over the years we have added a wide variety of different storages to our stack including PostgreSQL (some hosted by Heroku, some by Amazon RDS) for storing relational data, Amazon DynamoDB to store non-relational data like recommendations & user connections, or Redis to hold pre-aggregated data to speed up API endpoints.

    Since we started running Postgres ourselves on RDS instead of only using the managed offerings of Heroku, we've gained additional flexibility in scaling our application while reducing costs at the same time.

    We are also heavily testing Amazon RDS for Aurora in its Postgres-compatible version and will also give the new release of Aurora Serverless a try!

    #SqlDatabaseAsAService #NosqlDatabaseAsAService #Databases #PlatformAsAService

    See more
    Julien DeFrance
    Julien DeFrance
    Principal Software Engineer at Tophatter · | 16 upvotes · 375.4K views
    atSmartZipSmartZip
    Amazon DynamoDB
    Amazon DynamoDB
    Ruby
    Ruby
    Node.js
    Node.js
    AWS Lambda
    AWS Lambda
    New Relic
    New Relic
    Amazon Elasticsearch Service
    Amazon Elasticsearch Service
    Elasticsearch
    Elasticsearch
    Superset
    Superset
    Amazon Quicksight
    Amazon Quicksight
    Amazon Redshift
    Amazon Redshift
    Zapier
    Zapier
    Segment
    Segment
    Amazon CloudFront
    Amazon CloudFront
    Memcached
    Memcached
    Amazon ElastiCache
    Amazon ElastiCache
    Amazon RDS for Aurora
    Amazon RDS for Aurora
    MySQL
    MySQL
    Amazon RDS
    Amazon RDS
    Amazon S3
    Amazon S3
    Docker
    Docker
    Capistrano
    Capistrano
    AWS Elastic Beanstalk
    AWS Elastic Beanstalk
    Rails API
    Rails API
    Rails
    Rails
    Algolia
    Algolia

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

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    Interest over time
    Reviews of Amazon RDS for Aurora and Sequelize
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    How developers use Amazon RDS for Aurora and Sequelize
    Avatar of Ralic Lo
    Ralic Lo uses SequelizeSequelize

    Used it for full stack web application development, especially to interact with MySQL/ MariaDB / PostgreSQL server.

    Avatar of Secumail
    Secumail uses Amazon RDS for AuroraAmazon RDS for Aurora

    Managed MySQL clustered database so I dont have to deal with the required infrastructure

    Avatar of RedLine13
    RedLine13 uses Amazon RDS for AuroraAmazon RDS for Aurora

    Core database for managing users, teams, tests, and result summaries

    Avatar of Yaakov Gesher
    Yaakov Gesher uses Amazon RDS for AuroraAmazon RDS for Aurora

    We moved our database from compose.io to AWS for speed and price.

    Avatar of Bùi Thanh
    Bùi Thanh uses Amazon RDS for AuroraAmazon RDS for Aurora
    • Performance, HA and Scalable.
    • AutoScale replicas.
    Avatar of toby lin
    toby lin uses SequelizeSequelize

    ORM for mysql with express. so far so good

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