Abstract
Introducing a strong consistency model into NoSQL data storages is one of the most interesting issues nowadays. In spite of the CAP theorem, many NoSQL systems try to strengthen the consistency to their limits to better serve the business needs. However, many consistency-related problems that occur in popular data storages are impossible to overcome and enforce rebuilding the whole system from scratch. Additionally, providing scalability to those systems really complicates the matter. In this paper, a novel data storage architecture that supports strong consistency without loosing scalability is proposed. It provides strong consistency according to the following requirements: high scalability, high availability, and high throughput. The proposed solution is based on the Scalable Distributed Two–Layer Data Store which has proven to be a very efficient NoSQL system. The proposed architecture takes into account the concurrent execution of operations and unfinished operations. The theoretical correctness of the architecture as well as experimental evaluation in comparison to traditional mechanisms like locking and versioning is also shown. Comparative analysis with popular NoSQL systems like MongoDB and MemCached is also presented. Obtained results show that the proposed architecture presents a very high performance in comparison to existing NoSQL systems.
Highlights
Contemporary applications more and more frequently store and process large volumes of data
This paper presents an analysis of the consistency model of SD2DS
Orphan Body Inconsistency (OBI) 2: during concurrent execution of DEL(k) = CH → U1 → U2 and UPDATE (k, bk) = CH → O1 → U2 → Z2 the permanent OBI is caused by Z2, if and only if O1 → U1 and U2 → Z2, error appears in U2 or U2
Summary
Contemporary applications more and more frequently store and process large volumes of data. A rapidly growing number of big data applications requires efficient database architectures supporting scalability and availability for data analytics In such cases, simpler but more efficient datastores are widely used instead of RDBMS systems. Used techniques of horizontal scaling are: data replication, data partitioning, or distributed processing of requests As it was proved in [2], to achieve horizontal scalability, availability, and partition tolerance, database systems cannot impose strong consistency. A highly scalable datastore supporting strong consistency is presented and evaluated. The main contributions of this paper are two consistency models that are used with basic SD2DS architecture They allow ensuring strong consistency without affecting the scalability.
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