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Consistent read was a new feature that was released at the same time as conditional put and conditional delete. As the name suggests, consistent read addresses problems that arise due to SimpleDB's eventual consistency model (See the Limitations section). Consider the following sequence of operations: Program A stores some data in SimpleDB.
Examples include: File synchronization, such as syncing a hand-held MP3 player to a desktop computer; Cluster file systems, which are file systems that maintain data or indexes in a coherent fashion across a whole computing cluster; Cache coherency, maintaining multiple copies of data in sync across multiple caches;
Amazon DynamoDB is a managed NoSQL database service provided by Amazon Web Services (AWS). It supports key-value and document data structures and is designed to handle a wide range of applications requiring scalability and performance. [2]
Early AWS "building blocks" logo along a sigmoid curve depicting recession followed by growth. [citation needed]The genesis of AWS came in the early 2000s. After building Merchant.com, Amazon's e-commerce-as-a-service platform that offers third-party retailers a way to build their own web-stores, Amazon pursued service-oriented architecture as a means to scale its engineering operations, [15 ...
Elastic Volumes makes it possible to adapt volume size to an application's current needs, using Amazon CloudWatch and AWS Lambda to automate volume changes. Amazon EBS Encryption encrypts data at rest for EBS volumes and snapshots, without having to manage a separate secure key infrastructure.
Microsoft Sync Framework is a data synchronization platform from Microsoft that can be used to synchronize data across multiple data stores. Sync Framework includes a transport-agnostic architecture, into which data store-specific synchronization providers, modelled on the ADO.NET data provider API, can be plugged in. Sync Framework can be used for offline access to data, by working against a ...
Lambda Pinball" is a related anti-pattern that can occur in serverless architectures when functions (e.g., AWS Lambda, Azure Functions) excessively invoke each other in fragmented chains, leading to latency, debugging and testing challenges, and reduced observability. [4]
The Bekenstein bound limits the amount of information that can be stored within a spherical volume to the entropy of a black hole with the same surface area.; Thermodynamics limit the data storage of a system based on its energy, number of particles and particle modes.