Amazon Aurora is a relational database offered as a service in Amazon's AWS. Based on the open source version of MySQL, it is a commercial database that claims to be compatible with MySQL and PostgreSQL while providing superior throughput. Being provided as a cloud service, Aurora promises high availability by using distributed replications of backend storage. The system is being actively maintained and updated by Amazon.
Aurora was announced on Nov. 12, 2014 in Amazon's re:Invent conference in Las Vegas. It was officially released and ready to use as a service in AWS on July 27, 2015 by being added into the Amazon Relational Database Service. A major patch of Aurora was added in October 24, 2017, where Aurora was extended with PostgreSQL compatibility.
Multi-version Concurrency Control (MVCC)
Aurora decouples the storage engine from its database engine, and the concurrency control protocol is entirely decided by the database engine it used. In the paper that introduced Aurora, the concurrency control model was stated to be exactly the same as the database engine it inherited from. So Aurora has the same concurrency control protocol, MVCC, as MySQL/InnoDB does. InnoDB's MVCC protocol stores a separate data structure for "rollback segments", which are actually undo logs. In the situation of a consistent read (for isolation levels beyond read committed), the logs will be applied in place to reconstruct the requested earlier versions of a row.
Aurora has different join algorithm compared to MySQL. It supports hash join in addition to the already-existing nested loop join in MySQL. When the hash join option is enabled, Aurora's optimizer will automatically choose a join method as it evaluates the query plan. However, there are several restrictions for hash join in Aurora. To be more specific, left-right outer joins, semijoins such as subqueries and multiple-table updates or deletes are not supported.
Aurora's logging design is logical logging. The system separates the database engine from the backend storage, where the database engine propagates logs continuously to the backend storage. Such logs are then asynchronously processed by the distributed storage servers to bring the database to its latest state.
N-ary Storage Model (Row/Record)
Same as MySQL/InnoDB, Aurora is a row-storage DBMS. The tuples are stored row-by-row in the distributed storage servers.
Aurora decouples its database engine from the storage backend. The database engine is a modified version with MySQL/InnoDB, where the storage backend consists of distributed replicas that span across different availability zones in AWS. The database engine will propagates logs to the backend storage, and the backend storage utilizes a quorum based synchronization scheme to ensure the consistency of the database.
https://aws.amazon.com/rds/aurora/
https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Aurora.html
Amazon
2014