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data-intensive-application

Part one:

Think about data systems

• Store data so that they, or another application, can find it again later (databases)
• Remember the result of an expensive operation, to speed up reads (caches)
• Allow users to search data by keyword or filter it in various ways (search indexes)
• Send a message to another process, to be handled asynchronously (stream pro‐ cessing)
• Periodically crunch a large amount of accumulated data (batch processing)

  1. For example, there are datastores that are also used as mes‐ sage queues (Redis), and there are message queues with database-like durability guar‐ antees (Apache Kafka).

About Rest and Soap

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Replication

Why use replication?

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Master-slave model

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Synchronous & Asynchronous

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Fail

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Replication logs

Stream Processing

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