Distributed architecture of faunaDB: How to implement the distributed architecture of faunaDB in a distributed architecture

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Author: Zen and the Art of Computer Programming

1 Introduction

1.1 Why write this article?

faunaDB is a cloud-based relational database service developed and launched by Fauna Labs, which can meet the needs of various applications for relational databases. As a new cloud database product, its unique design concept and features have attracted the attention of many developers. In order to let more people understand the distributed architecture of faunaDB, this article will elaborate on its distributed architecture design.

1.2 What is faunaDB?

Fauna by FaunaLabs is a relational database service. Users only need to provide the required resources to run the Fauna service. FaunaDB is a distributed database. Under the distributed system architecture, it can deploy copies in multiple data centers to ensure high availability. The goal of Fauna is to enable developers to focus on core business logic without worrying about the complexity of the underlying infrastructure.

1.3 Why do we need the distributed architecture of faunaDB?

With the growth of enterprise applications, the capacity and processing power of a single database are no longer sufficient to support the growing data. Therefore, a distributed architecture pattern is required. Distributed architectures can help address data storage capacity issues and allow applications to scale to new, larger computing environments. At the same time, the distributed architecture also allows applications to achieve elastic scaling to cope with sudden traffic or concurrent requests. FaunaDB improves performance by using a clustering scheme on a distributed architecture.

2. Explanation of basic concepts and terms

2.1 Distributed database

A distributed database system means that the data is dispersedly distributed on different servers, and each node saves a complete data set. The advantage of this system is that it is highly scalable and can support the storage and access of massive data; the disadvantage is that it is expensive, because all data needs to be replicated to each node. Distributed database systems can