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Amazon Redshift is a data warehouse product which forms part of the larger cloud-computing platform Amazon Web Services. [1] It is built on top of technology from the massive parallel processing (MPP) data warehouse company ParAccel (later acquired by Actian ), [ 2 ] to handle large scale data sets and database migrations .
Amazon Relational Database Service (or Amazon RDS) is a distributed relational database service by Amazon Web Services (AWS). [2] It is a web service running "in the cloud" designed to simplify the setup, operation, and scaling of a relational database for use in applications. [ 3 ]
Amazon Aurora is a proprietary relational database offered as a service by Amazon Web Services (AWS) since October 2014. [ 1 ] [ 2 ] Aurora is available as part of the Amazon Relational Database Service (RDS).
For example, public requests may be routed to the blue server, making it the production server and the green server the staging server, which can only be accessed on a private network. Changes are installed on the non-live server, which is then tested through the private network to verify the changes work as expected.
Dynamo is a set of techniques that together can form a highly available key-value structured storage system [1] or a distributed data store. [1] It has properties of both databases and distributed hash tables (DHTs). It was created to help address some scalability issues that Amazon experienced during the holiday season of 2004. [2]
Amazon DynamoDB does not natively support join operations, as it is a NoSQL database optimized for single-table, high-performance access patterns. However, join-like operations can be achieved through integrations with external tools such as Amazon EMR, Amazon Athena, and Apache Spark.
The Amazon Neptune SLA policy is designed to offer a monthly uptime percentage greater that of 99.9%, increasing database performance and availability by integrating the engine with a virtual storage based on SSD drives, that are specially made for database workloads. Neptune maintains copies of the user's data in multiple Availability Zones.
Most schema migration tools aim to minimize the impact of schema changes on any existing data in the database. Despite this, preservation of data in general is not guaranteed because schema changes such as the deletion of a database column can destroy data (i.e. all values stored under that column for all rows in that table are deleted).