Amazon RDS聽vs聽DigitalOcean Managed Databases

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Amazon RDS
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Amazon RDS vs DigitalOcean Managed Databases: What are the differences?

Developers describe Amazon RDS as "Set up, operate, and scale a relational database in the cloud". 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. On the other hand, DigitalOcean Managed Databases is detailed as "Fully hosted and managed database engines for your applications, so you can focus on building, not patching". 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.

Amazon RDS and DigitalOcean Managed Databases can be categorized as "SQL Database as a Service" tools.

Some of the features offered by Amazon RDS are:

  • Pre-configured Parameters
  • Monitoring and Metrics
  • Automatic Software Patching

On the other hand, DigitalOcean Managed Databases provides the following key features:

  • Multi-node database clustering
  • Automated failover support
  • Daily backups with Point in Time Recovery (7 days)
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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 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.
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          What are some alternatives to Amazon RDS and DigitalOcean Managed Databases?
          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.
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          Decisions about Amazon RDS and DigitalOcean Managed Databases
          Tim Specht
          Tim Specht
          鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 58K 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 393.6K 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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          Reviews of Amazon RDS and DigitalOcean Managed Databases
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          How developers use Amazon RDS and DigitalOcean Managed Databases
          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.

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