Apache Aurora vs MySQL

Overview

Apache Aurora

Stacks69

Followers96

Votes0

MySQL

Stacks129.6K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

Apache Aurora vs MySQL: What are the differences?

Apache Aurora and MySQL are both database management systems, but they differ in their architecture and approach. Aurora, developed by Apache, is a distributed, fault-tolerant system designed for high availability and scalability. MySQL, on the other hand, is a popular open-source database known for its simplicity and flexibility, making it suitable for a wide range of applications. Here are the key differences between Apache Aurora and MySQL:

Architecture and Scale: Apache Aurora is a distributed and highly scalable system for managing and scheduling long-running services, while MySQL is a relational database management system (RDBMS) designed for structured data storage and retrieval. Aurora is built on top of Apache Mesos and is designed to handle large-scale deployments across a cluster of machines, providing fault tolerance and horizontal scalability. MySQL, on the other hand, is a standalone database system that can scale vertically by adding more resources to a single server.
Data Model and Query Language: Aurora is designed to work with distributed systems and provides a key-value store-like interface for managing services and tasks. It does not support SQL queries directly but can be used with other systems that provide SQL-like interfaces. MySQL, on the other hand, is a full-fledged relational database system that supports structured data with a rich set of data types, indexes, and SQL-based querying capabilities.
Replication and High Availability: Aurora uses a distributed storage system that replicates data across multiple nodes, ensuring data durability and availability even in the case of node failures. It provides automatic data replication and failover capabilities. MySQL, on the other hand, offers various replication options such as master-slave replication and multi-master replication. Replication setup and management in MySQL typically require more manual configuration compared to Aurora.
Ecosystem and Community: MySQL has a mature and widely adopted ecosystem with extensive community support, including a large number of third-party tools, libraries, and frameworks. Aurora, being a more specialized system, has a smaller community but is backed by the Apache Software Foundation.
Use Cases and Deployment Scenarios: Aurora is primarily designed for managing and scaling long-running services in a distributed environment. It is well-suited for microservices architectures and cloud-native applications. On the other hand, MySQL is a general-purpose database system that can be used for a wide range of applications, including web applications, enterprise systems, and data-driven applications.

In summary, if you are building a distributed system with a need for high scalability, fault tolerance, and automatic failover, Aurora may be a suitable choice. If you require a more traditional relational database management system with a mature ecosystem and broader community support, MySQL would be a better fit.

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Advice on Apache Aurora, MySQL

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

Apache Aurora	MySQL
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.	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.
Deployment and scheduling of jobs;The abstraction a “job” to bundle and manage Mesos tasks;A rich DSL to define services;Health checking;Failure domain diversity;Instant provisioning	-
Statistics
GitHub Stars -	GitHub Stars 11.8K
GitHub Forks -	GitHub Forks 4.1K
Stacks 69	Stacks 129.6K
Followers 96	Followers 108.6K
Votes 0	Votes 3.8K
Pros & Cons
No community feedback yet	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
Integrations
Apache Mesos Vagrant	No integrations available

What are some alternatives to Apache Aurora, MySQL?

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.

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.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

Related Comparisons

Architecture and Scale: Apache Aurora is a distributed and highly scalable system for managing and scheduling long-running services, while MySQL is a relational database management system (RDBMS) designed for structured data storage and retrieval. Aurora is built on top of Apache Mesos and is designed to handle large-scale deployments across a cluster of machines, providing fault tolerance and horizontal scalability. MySQL, on the other hand, is a standalone database system that can scale vertically by adding more resources to a single server.
Data Model and Query Language: Aurora is designed to work with distributed systems and provides a key-value store-like interface for managing services and tasks. It does not support SQL queries directly but can be used with other systems that provide SQL-like interfaces. MySQL, on the other hand, is a full-fledged relational database system that supports structured data with a rich set of data types, indexes, and SQL-based querying capabilities.
Replication and High Availability: Aurora uses a distributed storage system that replicates data across multiple nodes, ensuring data durability and availability even in the case of node failures. It provides automatic data replication and failover capabilities. MySQL, on the other hand, offers various replication options such as master-slave replication and multi-master replication. Replication setup and management in MySQL typically require more manual configuration compared to Aurora.
Ecosystem and Community: MySQL has a mature and widely adopted ecosystem with extensive community support, including a large number of third-party tools, libraries, and frameworks. Aurora, being a more specialized system, has a smaller community but is backed by the Apache Software Foundation.
Use Cases and Deployment Scenarios: Aurora is primarily designed for managing and scaling long-running services in a distributed environment. It is well-suited for microservices architectures and cloud-native applications. On the other hand, MySQL is a general-purpose database system that can be used for a wide range of applications, including web applications, enterprise systems, and data-driven applications.

Apache Aurora vs MySQL