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Distributed Spring Batch without a Message Broker
Distributed Spring Batch partitioning already needs a shared, persistent job repository. This article makes that database the whole coordination plane and drops the message broker, sizing work to the live node count, a per-job master with no standing coordinator, compare-and-set claiming that prevents double-execution, two-phase heartbeat failover, and where a broker is still the right choice.
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The Next Evolution of the Database Sharding Architecture
In this article, author Juan Pan discusses the data sharding architecture patterns in a distributed database system. She explains how Apache ShardingSphere project solves the data sharding challenges. Also discussed are two practical examples of how to create a distributed database and an encrypted table with DistSQL.
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CAP Twelve Years Later: How the "Rules" Have Changed
The CAP theorem asserts that any networked shared-data system can have only two of three desirable properties (Consistency, Availability and Partition Tolerance). In this IEEE article, author Eric Brewer discusses how designers can optimize consistency and availability by explicitly handling partitions, thereby achieving some trade-off of all three.
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Finding the Right Data Solution for Your Application in the Data Storage Haystack
With the recent NoSQL movement there are several alternative data storage solutions available compared to the traditional relational databases. In this article, author Srinath Perera discusses the various data storage options and what to consider when choosing each of these solutions.