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Decisions about Amazon Aurora, Amazon RDS, and Google Cloud SQL
Phillip Manwaring
Developer at Coach Align · | 5 upvotes · 27.9K 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
Manage your open source components, licenses, and vulnerabilities
Learn MorePros of Amazon Aurora
Pros of Amazon RDS
Pros of Google Cloud SQL
Pros of Amazon Aurora
- MySQL compatibility14
- Better performance12
- Easy read scalability10
- Speed9
- Low latency read replica7
- High IOPS cost2
- Good cost performance1
Pros of Amazon RDS
- Reliable failovers165
- Automated backups156
- Backed by amazon130
- Db snapshots92
- Multi-availability87
- Control iops, fast restore to point of time30
- Security28
- Elastic24
- Push-button scaling20
- Automatic software patching20
- Replication4
- Reliable3
- Isolation2
Pros of Google Cloud SQL
- Fully managed13
- Backed by Google10
- SQL10
- Flexible4
- Encryption at rest and transit3
- Automatic Software Patching3
- Replication across multiple zone by default3
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Cons of Amazon Aurora
Cons of Amazon RDS
Cons of Google Cloud SQL
Cons of Amazon Aurora
- Vendor locking2
- Rigid schema1
Cons of Amazon RDS
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Cons of Google Cloud SQL
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What is Amazon 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 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?
Run the same relational databases you know with their rich extension collections, configuration flags and developer ecosystem, but without the hassle of self management.
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What companies use Amazon Aurora?
What companies use Amazon RDS?
What companies use Google Cloud SQL?
What companies use Amazon Aurora?
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What tools integrate with Amazon Aurora?
What tools integrate with Amazon RDS?
What tools integrate with Google Cloud SQL?
What tools integrate with Amazon Aurora?
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What are some alternatives to Amazon Aurora, Amazon RDS, and Google Cloud SQL?
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.
PostgreSQL
PostgreSQL is an advanced object-relational database management system
that supports an extended subset of the SQL standard, including
transactions, foreign keys, subqueries, triggers, user-defined types
and functions.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
Amazon S3
Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web