Amazon RDS vs Google Cloud SQL

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Amazon RDS

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Amazon RDS vs Google Cloud SQL: 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, Google Cloud SQL is detailed as "Store and manage data using a fully-managed, relational MySQL database". 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.

Amazon RDS and Google Cloud SQL can be primarily classified 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, Google Cloud SQL provides the following key features:

  • Familiar Infrastructure
  • Flexible Charging
  • Security, Availability, Durability

"Reliable failovers" is the primary reason why developers consider Amazon RDS over the competitors, whereas "Fully managed" was stated as the key factor in picking Google Cloud SQL.

According to the StackShare community, Amazon RDS has a broader approval, being mentioned in 1408 company stacks & 509 developers stacks; compared to Google Cloud SQL, which is listed in 71 company stacks and 28 developer stacks.

Decisions about Amazon RDS and Google Cloud SQL
Phillip Manwaring
Developer at Coach Align · | 5 upvotes · 6K views

Using on-demand read/write capacity while we scale our userbase - means that we're well within the free-tier on AWS while we scale the business and evaluate traffic patterns.

Using single-table design, which is dead simple using Jeremy Daly's dynamodb-toolbox library

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Pros of Amazon RDS
Pros of Google Cloud SQL
  • 163
    Reliable failovers
  • 154
    Automated backups
  • 129
    Backed by amazon
  • 92
    Db snapshots
  • 86
    Multi-availability
  • 29
    Control iops, fast restore to point of time
  • 27
    Security
  • 23
    Elastic
  • 20
    Automatic software patching
  • 20
    Push-button scaling
  • 4
    Replication
  • 3
    Reliable
  • 2
    Isolation
  • 13
    Fully managed
  • 10
    SQL
  • 10
    Backed by Google
  • 4
    Flexible
  • 3
    Encryption at rest and transit
  • 3
    Replication across multiple zone by default
  • 3
    Automatic Software Patching

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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 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.

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What companies use Amazon RDS?
What companies use Google Cloud SQL?
See which teams inside your own company are using Amazon RDS or Google Cloud SQL.
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What tools integrate with Google Cloud SQL?

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What are some alternatives to Amazon RDS 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.
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How developers use Amazon RDS and Google Cloud SQL
Pathwright uses
Amazon 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.

AngeloR uses
Amazon 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.

Wirkn Inc. uses
Amazon RDS

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

Digital2Go uses
Amazon RDS

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

fadingdust uses
Amazon RDS

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

Casey Smith uses
Google Cloud SQL

Back-end datastore.