Amazon RDS聽vs聽ClearDB聽vs聽Google Cloud SQL

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Amazon RDS
Amazon RDS

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ClearDB
ClearDB

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Google Cloud SQL
Google Cloud SQL

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What is 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.

What is 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.

What is Google Cloud SQL?

MySQL databases deployed in the cloud without a fuss. Google Cloud Platform provides you with powerful databases that run fast, don鈥檛 run out of space and give your application the redundant, reliable storage it needs.
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        What companies use Amazon RDS?
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        What are some alternatives to Amazon RDS, ClearDB, and Google Cloud SQL?
        Amazon Redshift
        It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
        Apache Aurora
        Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
        MySQL
        The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
        Oracle
        Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
        Heroku Postgres
        Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
        See all alternatives
        Decisions about Amazon RDS, ClearDB, and Google Cloud SQL
        Tim Specht
        Tim Specht
        鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 81.3K views
        atDubsmashDubsmash
        PostgreSQL
        PostgreSQL
        Heroku
        Heroku
        Amazon RDS
        Amazon RDS
        Amazon DynamoDB
        Amazon DynamoDB
        Redis
        Redis
        Amazon RDS for Aurora
        Amazon RDS for Aurora
        #SqlDatabaseAsAService
        #NosqlDatabaseAsAService
        #Databases
        #PlatformAsAService

        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 1.1M views
        atSmartZipSmartZip
        Rails
        Rails
        Rails API
        Rails API
        AWS Elastic Beanstalk
        AWS Elastic Beanstalk
        Capistrano
        Capistrano
        Docker
        Docker
        Amazon S3
        Amazon S3
        Amazon RDS
        Amazon RDS
        MySQL
        MySQL
        Amazon RDS for Aurora
        Amazon RDS for Aurora
        Amazon ElastiCache
        Amazon ElastiCache
        Memcached
        Memcached
        Amazon CloudFront
        Amazon CloudFront
        Segment
        Segment
        Zapier
        Zapier
        Amazon Redshift
        Amazon Redshift
        Amazon Quicksight
        Amazon Quicksight
        Superset
        Superset
        Elasticsearch
        Elasticsearch
        Amazon Elasticsearch Service
        Amazon Elasticsearch Service
        New Relic
        New Relic
        AWS Lambda
        AWS Lambda
        Node.js
        Node.js
        Ruby
        Ruby
        Amazon DynamoDB
        Amazon DynamoDB
        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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        How developers use Amazon RDS, ClearDB, and Google Cloud SQL
        Avatar of Pathwright
        Pathwright uses Amazon RDSAmazon RDS

        While we initially started off running our own Postgres cluster, we evaluated RDS and found it to be an excellent fit for us.

        The failovers, manual scaling, replication, Postgres upgrades, and pretty much everything else has been super smooth and reliable.

        We'll probably need something a little more complex in the future, but RDS performs admirably for now.

        Avatar of AngeloR
        AngeloR uses Amazon RDSAmazon RDS

        We are using RDS for managing PostgreSQL and legacy MSSQL databases.

        Unfortunately while RDS works great for managing the PostgreSQL systems, MSSQL is very much a second class citizen and they don't offer very much capability. Infact, in order to upgrade instance storage for MSSQL we actually have to spin up a new cluster and migrate the data over.

        Avatar of Wirkn Inc.
        Wirkn Inc. uses Amazon RDSAmazon RDS

        Our PostgreSQL servers, where we keep the bulk of Wirkn data, are hosted on the fantastically easy and reliable AWS RDS platform.

        Avatar of Digital2Go
        Digital2Go uses Amazon RDSAmazon RDS

        We use Aurora for our OLTP database, it provides significant speed increases on top of MySQL without the need to manage it

        Avatar of fadingdust
        fadingdust uses Amazon RDSAmazon RDS

        RDS allows us to replicate the development databases locally as well as making it available to CircleCI.

        Avatar of Casey Smith
        Casey Smith uses Google Cloud SQLGoogle Cloud SQL

        Back-end datastore.

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