Issue link: https://resources.awscloud.com/i/1496542
©2020 IDC #US47078920 6 Graph Data Management (Amazon Neptune) Amazon Neptune enables support for complex property graphs that may contain billions of nodes and edges. It supports the W3C RDF and SPARQL standards as well as Apache TinkerPop and Gremlin. Graphs can be used to perform content semantic analysis, classify information on real-world people or objects, perform complex relationship pattern recognition, and detect multilevel associations and patterns of associations. Common use cases for Amazon Neptune include recommendation engines, social network analysis, IT operational network management and analysis, and life sciences research. Graphs are used to build customer 360 solutions to understand the customer journey; provide social recommendations on people to follow, places to visit, or restaurants to try; understand data lineage; understand patterns of fraud from transactions with users, devices, or credit cards; integrate and analyze data across silos; or enforce data access using relationships between users, data, and policies. Wide Column (Amazon Keyspaces for Apache Cassandra) A wide column store offers a NoSQL database wherein the data is organized into groups of columns, called column families, and can be treated as tables or two-dimensional key-value store data. Apache Cassandra is the most popular wide column store, and Amazon Keyspaces (for Apache Cassandra) is a managed database service that offers complete, compatible support for Cassandra databases and workloads. Amazon Keyspaces supports the Cassandra Query Language (CQL) as well as the drivers and developer tools built for Apache Cassandra. Amazon Keyspaces is serverless, so there is no infrastructure or software to manage. The data is encrypted and replicated three times in multiple AWS AZs for high availability. Amazon Keyspaces also enables you to create continuous backups of your table data by using point-in-time recovery. In-Memory Data Store (Amazon ElastiCache) Amazon ElastiCache is a fully managed in-memory data store that offers shared in-memory data management for either data sharing among application processes or holding and retrieving data using low-latency in-memory data stores. It includes support for the popular open source data cache technologies, Redis and Memcached, and is fully managed by AWS, which handles monitoring, failure recovery, backups, and other operational tasks. Amazon ElastiCache uses an end-to-end optimized stack running on customer-dedicated nodes for fast, secure performance. Specialized Data Management Time Series (Amazon Timestream) Time series data requires special handling because its regular interval-based data is used for detailed statistical pattern analysis. Query and analysis need to have the appropriate math built in, and time series data must be append only and immutable. The most common use cases involve IoT device data, IT logs, and the output from smart industrial machines. Amazon Timestream is a purpose-built time series database designed from the ground up to serve this purpose. Timestream offers a built-in analytic capability and automates retention, tiering, and compression of data to minimize data management costs. It also employs a serverless architecture to match resource utilization to the application requirement.