Database Sharding - Scaling Relational Databases скачать в хорошем качестве

Database Sharding - Scaling Relational Databases

RDBMs can be scaled horizontally in a number of ways, however two most most common ways are Read scale out and Sharding. Sharding is a technique to distribute large amounts of identically structured data across a number of independent databases. It is especially popular with cloud developers creating Software as a Service (SAAS) offerings for end customers or businesses. These end customers are often referred to as "tenants". Sharding may be required for any number of reasons: The total amount of data is too large to fit within the constraints of an individual database The transaction throughput of the overall workload exceeds the capabilities of an individual database Tenants may require physical isolation from each other, so separate databases are needed for each tenant Different sections of a database may need to reside in different geographies for compliance, performance, or geopolitical reasons. In this episode I introduce the various techniques but focus primarily on Sharding. Horizontal scaling refers to adding or removing databases in order to adjust capacity or overall performance, also called "scaling out". Sharding, in which data is partitioned across a collection of identically structured databases, is a common way to implement horizontal scaling.