Amazon RDS for Aurora vs MySQL

Overview

MySQL

Stacks129.6K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

Amazon Aurora

Stacks804

Followers744

Votes55

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

Amazon RDS for Aurora and MySQL are both popular relational database management systems used for storing and managing data. Here are the key differences between the two.

Performance and Scalability: Amazon RDS for Aurora offers higher performance and scalability compared to MySQL. Aurora uses a distributed storage system that automatically scales up to 64 terabytes and can handle up to millions of transactions per minute. MySQL, on the other hand, has limitations on scalability and performance based on the hardware it is installed on.
High Availability: Amazon RDS for Aurora provides higher availability compared to MySQL. It replicates six copies of your data across three Availability Zones and continuously backs up your data to Amazon S3. In case of a failure, Aurora automatically fails over to a replica, minimizing downtime. MySQL relies on traditional replication methods, which may not provide the same level of availability.
Backup and Recovery: Amazon RDS for Aurora offers faster backup and recovery options compared to MySQL. Aurora continuously backs up your data to Amazon S3, enabling point-in-time recovery with a granularity of one second. MySQL requires manual configuration of backup and recovery processes, which may not be as efficient or granular.
Compatibility and Portability: MySQL is more compatible and portable compared to Amazon RDS for Aurora. Aurora is based on an enhanced version of MySQL, but it has some differences and optimizations that may require modifications to your applications. MySQL allows for easier migration between different database systems, whereas Aurora may require more effort to migrate to another platform.
Self Healing: Amazon RDS for Aurora has self-healing capabilities that make it more resilient to failures compared to MySQL. It constantly monitors the health of your database instances and automatically repairs common issues without downtime. MySQL requires manual intervention for troubleshooting and fixing issues.
Cost: Amazon RDS for Aurora may have higher costs compared to MySQL, depending on your specific use case. Aurora offers higher performance and availability, but it comes at a higher price point compared to MySQL. Consider your application requirements and budget before choosing between the two options.

In summary, Amazon RDS for Aurora offers superior performance, availability, and backup and recovery options compared to MySQL. However, it may require modifications to your applications and comes at a higher cost. MySQL, on the other hand, offers easier compatibility and portability but may lack some of the advanced features of Amazon RDS for Aurora.

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Advice on MySQL, Amazon Aurora

Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

Decidedon

PostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k

Comments

Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k

Comments

Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceon

MySQL

PostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k

Comments

Detailed Comparison

MySQL	Amazon Aurora
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.	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.
-	High Throughput with Low Jitter;Push-button Compute Scaling;Storage Auto-scaling;Amazon Aurora Replicas;Instance Monitoring and Repair;Fault-tolerant and Self-healing Storage;Automatic, Continuous, Incremental Backups and Point-in-time Restore;Database Snapshots;Resource-level Permissions;Easy Migration;Monitoring and Metrics
Statistics
GitHub Stars 11.8K	GitHub Stars -
GitHub Forks 4.1K	GitHub Forks -
Stacks 129.6K	Stacks 804
Followers 108.6K	Followers 744
Votes 3.8K	Votes 55
Pros & Cons
Pros 800 Sql 679 Free 562 Easy 528 Widely used 490 Open source Cons 16 Owned by a company with their own agenda 3 Can't roll back schema changes	Pros 14 MySQL compatibility 12 Better performance 10 Easy read scalability 9 Speed 7 Low latency read replica Cons 2 Vendor locking 1 Rigid schema
Integrations
No integrations available	PostgreSQL

What are some alternatives to MySQL, Amazon Aurora?

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.

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.

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.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

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

Amazon RDS for Aurora and MySQL are both popular relational database management systems used for storing and managing data. Here are the key differences between the two.

Performance and Scalability: Amazon RDS for Aurora offers higher performance and scalability compared to MySQL. Aurora uses a distributed storage system that automatically scales up to 64 terabytes and can handle up to millions of transactions per minute. MySQL, on the other hand, has limitations on scalability and performance based on the hardware it is installed on.
High Availability: Amazon RDS for Aurora provides higher availability compared to MySQL. It replicates six copies of your data across three Availability Zones and continuously backs up your data to Amazon S3. In case of a failure, Aurora automatically fails over to a replica, minimizing downtime. MySQL relies on traditional replication methods, which may not provide the same level of availability.
Backup and Recovery: Amazon RDS for Aurora offers faster backup and recovery options compared to MySQL. Aurora continuously backs up your data to Amazon S3, enabling point-in-time recovery with a granularity of one second. MySQL requires manual configuration of backup and recovery processes, which may not be as efficient or granular.
Compatibility and Portability: MySQL is more compatible and portable compared to Amazon RDS for Aurora. Aurora is based on an enhanced version of MySQL, but it has some differences and optimizations that may require modifications to your applications. MySQL allows for easier migration between different database systems, whereas Aurora may require more effort to migrate to another platform.
Self Healing: Amazon RDS for Aurora has self-healing capabilities that make it more resilient to failures compared to MySQL. It constantly monitors the health of your database instances and automatically repairs common issues without downtime. MySQL requires manual intervention for troubleshooting and fixing issues.
Cost: Amazon RDS for Aurora may have higher costs compared to MySQL, depending on your specific use case. Aurora offers higher performance and availability, but it comes at a higher price point compared to MySQL. Consider your application requirements and budget before choosing between the two options.

Amazon RDS for Aurora vs MySQL

Overview