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Consistency Model - Comparing the Use of Amazon DynamoDB and Apache HBase for NoSQL
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Consistency Model

A database consistency model determines the manner and timing in which a successful write or update is reflected in a subsequent read operation of that same value.

Amazon DynamoDB lets you specify the desired consistency characteristics for each read request within an application. You can specify whether a read is eventually consistent or strongly consistent.

The eventual consistency option is the default in Amazon DynamoDB and maximizes the read throughput. However, an eventually consistent read might not always reflect the results of a recently completed write. Consistency across all copies of data is usually reached within a second.

A strongly consistent read in Amazon DynamoDB returns a result that reflects all writes that received a successful response prior to the read. To get a strongly consistent read result, you can specify optional parameters in a request. It takes more resources to process a strongly consistent read than an eventually consistent read. For more information about read consistency, see Data Read and Consistency Considerations.

Apache HBase reads and writes are strongly consistent. This means that all reads and writes to a single row in Apache HBase are atomic. Each concurrent reader and writer can make safe assumptions about the state of a row. Multi-versioning and time stamping in Apache HBase contribute to its strongly consistent model.

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