Traquest Model

Atomicity, consistency, isolation and durability are essential properties of many distributed systems. They are often abbreviated as the ACID properties. Ensuring ACID comes with a price: it requires extra computing and network capacity to ensure that the atomic operations are done perfectly, or they are rolled back. When we have higher requirements on performance, we need to give up the ACID properties entirely or settle for eventual consistency. Since the ambiguity of the order of the events, such algorithms can get very complicated since they have to be prepared for any possible contingencies. Traquest model is an attempt for creating a general concurrency model that can bring the ACID properties without sacrificing a too significant amount of performance.

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Concurrency Model for Distributed Systems

Journal of Parallel and Distributed Computing ◽

10.1006/jpdc.1999.1583 ◽

1999 ◽

Vol 59 (3) ◽

pp. 445-464

Author(s):

Myungchul Kim ◽

Samuel T. Chanson ◽

Son T. Vuong

Keyword(s):

Distributed Systems ◽

Concurrency Model

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Speed for the Elite, Consistency for the Masses: Differentiating Eventual Consistency in Large-Scale Distributed Systems

2016 IEEE 35th Symposium on Reliable Distributed Systems (SRDS) ◽

10.1109/srds.2016.032 ◽

2016 ◽

Author(s):

Davide Frey ◽

Achour Mostefaoui ◽

Matthieu Perrin ◽

Pierre-Louis Roman ◽

Francois Taiani

Keyword(s):

Distributed Systems ◽

Large Scale ◽

Eventual Consistency ◽

The Masses

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A Review of Polyglot Persistence in the Big Data World

Information ◽

10.3390/info10040141 ◽

2019 ◽

Vol 10 (4) ◽

pp. 141 ◽

Cited By ~ 3

Author(s):

Pwint Phyu Khine ◽

Zhaoshun Wang

Keyword(s):

Big Data ◽

Distributed Systems ◽

Query Language ◽

Point Of View ◽

Data Systems ◽

Data Intensive ◽

Soft State ◽

Eventual Consistency ◽

Big Data Systems ◽

The Relationship

The inevitability of the relationship between big data and distributed systems is indicated by the fact that data characteristics cannot be easily handled by a standalone centric approach. Among the different concepts of distributed systems, the CAP theorem (Consistency, Availability, and Partition Tolerant) points out the prominent use of the eventual consistency property in distributed systems. This has prompted the need for other, different types of databases beyond SQL (Structured Query Language) that have properties of scalability and availability. NoSQL (Not-Only SQL) databases, mostly with the BASE (Basically Available, Soft State, and Eventual consistency), are gaining ground in the big data era, while SQL databases are left trying to keep up with this paradigm shift. However, none of these databases are perfect, as there is no model that fits all requirements of data-intensive systems. Polyglot persistence, i.e., using different databases as appropriate for the different components within a single system, is becoming prevalent in data-intensive big data systems, as they are distributed and parallel by nature. This paper reflects the characteristics of these databases from a conceptual point of view and describes a potential solution for a distributed system—the adoption of polyglot persistence in data-intensive systems in the big data era.

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Verifying strong eventual consistency in distributed systems

Proceedings of the ACM on Programming Languages ◽

10.1145/3133933 ◽

2017 ◽

Vol 1 (OOPSLA) ◽

pp. 1-28 ◽

Cited By ~ 14

Author(s):

Victor B. F. Gomes ◽

Martin Kleppmann ◽

Dominic P. Mulligan ◽

Alastair R. Beresford

Keyword(s):

Distributed Systems ◽

Eventual Consistency

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NoSQL- A Solution for Handling Big Data

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a9896.109119 ◽

2019 ◽

Vol 9 (1) ◽

pp. 7606-7610

Keyword(s):

Big Data ◽

Special Reference ◽

Unstructured Data ◽

Huge Amount ◽

Nosql Databases ◽

Acid Properties ◽

Distributed Framework ◽

Soft State ◽

Different Types ◽

Eventual Consistency

The data produced nowadays is the Big data which is unstructured, semi-structured or structured in nature. It is difficult for SQL to handle such large amount of data with varied forms so NoSQL was introduced which gives many advantages over SQL. It is a schema less database which allows horizontal scaling, scalability and distributed framework. SQL is based on ACID properties (Atomicity, Consistency, Isolation, Durability) whereas NoSQL is based on BASE (Basic Availability, Soft state, Eventual consistency). This paper introduces the concepts of NoSQL, advantages of NoSQL over SQL, different types of NoSQL databases with special reference to the document store database, MongoDB. It explains in detail about the MongoDB and then experimentally evaluates the performance of the queries executed in SQL and NoSQL (MongoDB). The experiment conducted shows that NoSQL queries are executed faster as compared to SQL queries and can also handle huge amount of unstructured data very effortlessly and easily.

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