Issue link: https://resources.awscloud.com/i/1496553
©2020 IDC #US46773920 5 AWS DBMSs That Refactor Your Database Workloads Refactoring data means putting it in a format that is usable for all the workloads to be supported, both old and new. This may mean moving beyond relational databases designed for OLTP or OLAP to something that anticipates new challenges. In such cases, data will be enhanced or transformed to serve additional purposes. Sometimes, the best option is to implement a more agile approach, such as a key value store. In some cases, all the data from the on-premises system may stay together in a homogeneous format; in other cases, the data may be allocated to a variety of heterogeneous formats. The principal technologies in question include the following: ▪ Amazon Aurora. This managed relational DBMS is both MySQL and PostgreSQL compatible, provides the full capabilities of an enterprise RDBMS, and is optimized for performance, scalability, and high availability beyond what is possible with community open source relational database technology. Amazon Aurora is managed by Amazon Relational Database Service (Amazon RDS), which automates administrative tasks such as database setup, patching, and backups. It supports six open source and commercial database engines. ▪ Amazon Redshift. This DBMS is designed for analytics workloads, with a columnar architecture that stores data efficiently for fast query performance. It also has features to easily query data in operational databases and data lakes. ▪ Amazon DynamoDB. This fully managed NoSQL database service provides fast and predictable performance with seamless scalability. It is a multiregion, multimaster, and durable database for internet-scale applications with built-in security, backup, and restore. Key use cases are serverless web apps, massively multiplayer games, mobile back ends, media metadata, event-driven transactions, and microservices. In some cases, the data may be applied to more specialized purposes. AWS offers Amazon EMR for data lake management, Amazon DocumentDB (with MongoDB compatibility) for document database management, Amazon Neptune for graph analysis, Amazon KeySpaces (for Apache Cassandra), and Amazon ElastiCache, which is compatible with Redis or Memcached, for in-memory shared operational data. AWS Data Migration Services AWS offers a full range of data migration services to help in breaking free from legacy environments to AWS data management in the cloud. These services, driven by self-service tools, guide clients through the process of the following: ▪ Assessing the data and application portfolio to determine what to move and what to transform ▪ Achieving overall organizational commitment to the migration, including full support from the database administration team ▪ Working out a plan and timeline for stepwise migrations that deliver continuous benefits while minimizing risk In addition, there is a plethora of partners in the Amazon Partners Network (APN) and programs such as Database Freedom and Amazon Database Migration Accelerator to help enterprises on the way to an efficient, integrated, and cloud-based future.